Applications of Social Network Analysis For Building Community Disaster Resilience Workshop
Applications of Social Network Analysis For Building Community Disaster Resilience Workshop
Applications of Social Network Analysis For Building Community Disaster Resilience Workshop
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vi
Acknowledgments
vii
This workshop summary has been reviewed in draft form by persons chosen for their
diverse perspectives and technical expertise in accordance with procedures approved by the
National Research Council’s Report Review Committee. The purposes of this review are to
provide candid and critical comments that will assist the institution in making the published
summary as sound as possible and to ensure that the summary meets institutional standards of
objectivity, evidence, and responsiveness to the study charge. The review comments and draft
manuscript remain confidential to protect the integrity of the deliberative process. We wish to
thank the following for their participation in the review of this summary:
Although the reviewers listed above have provided many constructive comments and
suggestions, they were not asked to endorse, nor did they see, the final draft of the workshop
summary before its release. The review of this summary was overseen by the Division on Earth
and Life Studies. The division was responsible for making certain that an independent
examination of this summary was carried out in accordance with institutional procedures and that
all review comments were carefully considered. Responsibility for the final content of this
summary rests entirely with the author and the National Research Council.
Contents
SUMMARY 1
1 INTRODUCTION 9
Workshop Planning, 11
Workshop Summary Organization, 12
ix
REFERENCES 55
APPENDIXES
A Committee Biographies 57
B Selected Recent References on Disaster Resilience, Social Networks, and Social
Network Analysis 61
C Workshop Participants 67
D Breakout Session Descriptions 69
Summary
________________________________________________________________________
Social Network Analysis (SNA) is the identification of the relationships and attributes
of members, key actors, and groups that social networks comprise. The National
Research Council (NRC), at the request of the Department of Homeland Security (DHS),
formed an ad hoc committee to plan a two-day workshop on the use of SNA for the
purpose of building community disaster resilience. The workshop, held February 11-12,
2009, was designed to provide guidance to the DHS on a potential research agenda that
would increase the effectiveness of SNA for improving community disaster resilience.
Explored were the state of the art in SNA and its applications in the identification,
construction, and strengthening of networks within U.S. communities. Workshop
participants discussed current work in SNA focused on characterizing networks; the
theories, principles and research applicable to the design or strengthening of networks;
the gaps in knowledge that prevent the application of SNA to the construction of
networks; and research areas that could fill those gaps. Elements of a research agenda to
support the design, development, and implementation of social networks for the specific
purpose of strengthening community resilience against natural and human-made disasters
would be discussed. Box S-1 provides definitions of terms commonly used during the
workshop.
WORKSHOP PLANNING
A planning committee designed the workshop to explore how SNA could be applied
during all phases of the disaster cycle. The planning committee invited researchers with
expertise in resilience science and in SNA for a variety of applications (e.g., anti-
terrorism and public health) to participate in the workshop and discuss the states of the art
and science in their respective fields. Emergency management practitioners with experi-
ence responding to disasters were invited so that the needs of community leaders with
their “boots on the ground” could be considered. The committee included
participants from different geographical regions and with varying disaster experiences so
that a broad range of issues and perspectives could be explored.
Sessions of the workshop were devoted to specific themes. In the context of disaster
preparedness, the roles of SNA and communication in enhancing the functional, struc-
tural, and interactional connections between networks were discussed. Barriers to the use
of SNA for planning activities that decrease the impact of disasters (e.g., interventions)
were also discussed. Workshop participants considered how SNA could be used to make
network ties between organizations more productive, and how SNA could be applied
during and following a disaster to make improvisational responses—those planned once
needs and resources are identified—more flexible. How individuals and communities
could be engaged to promote collective behavior when preparing for, responding to, and
recovering from disasters was considered.
BOX S-1
Definitions of Key Workshop Terms
The following are definitions of key terms used in the study of social networks, social network
analysis, resiliency science, and research translation used during this workshop.
Resilience. The response to stress at individual, institutional, and societal levels categorized as
the characteristics that promote successful adaptation to adversity.
Social network. The interactions between people and organizations, including who knows, works
with, or communicates with whom, that can be mapped. The data and information found on tools
such as Facebook and the Enron Email Corpus are examples of social networks.
Social network analysis. The process of analyzing a social network and identifying key actors,
groups, vulnerabilities, and redundancies as well as the changes in these variables.
Social networking. The process of creating, maintaining, or altering one’s network and to one’s
advantage by using the network to gain resources or influence, or to mobilize activity.
Social network analysis tools. The set of tools, technologies, metrics, models, and visualization
techniques used for social network analysis. These may include data extraction tools, link analy-
sis, statistical techniques, and graph theory techniques using programs such as AutoMap, ORA,
UCINET, and Pajek.
Social network theory. The set of theories for forecasting, reasoning about, and understanding
how social networks form, are maintained, and evolve, and the role of variables such as social
networking tools, media, and stress in affecting the emergence, utilization, management, and
change in social networks.
Social network tools. A set of computational techniques that enable individuals and groups to
engage in social networking by monitoring and interacting within the networks with which they are
connected. Facebook, MySpace, and Twitter are examples of social networking tools.
Translation research. The research aimed at enhancing the movement of research results from
the scientific to the applied realms.
SUMMARY 3
WORKSHOP SUMMARY
This document summarizes the major points and ideas expressed during the workshop
as documented by the rapporteur. As such, the summary reflects the specific topics em-
phasized by workshop presentations and discussions and may not be a comprehensive
summary of all relevant topics and issues. Viewpoints expressed in this summary do not
necessarily represent the views of the workshop planning committee or the NRC, nor
does the summary contain conclusions or recommendations.
A robust scientific literature on SNA exists, and literature in disaster and community
resilience is emergent. However, workshop participants noted that disjunctions exist be-
tween SNA theory and its application, and between the SNA research and emergency
management communities. Workshop participants discussed how properly targeted re-
search in networking theory, the social and resiliency sciences, and research translation,
conducted in parallel with the development of SNA tools designed specifically for and
with emergency management practitioners, could facilitate the adoption of SNA by the
emergency management community. The adoption of SNA has the potential to revolu-
tionize the way organizations and communities function in general, and prepare and re-
spond to disasters in specific.
SNA allows study of complex human systems through the visualization and charac-
terization of relationships between people, groups, and organizations. A graphical repre-
sentation of a social network that shows individual network members (defined as nodes)
and their linkages (defined as ties) could be a product of the analysis (see Figure S-1).
The impact of information or activities on individuals and the network as a whole may be
analyzed and predicted for different scenarios and options. Because SNA can reveal the
characteristics, composition, and structure of networks at a given time and over time,
SNA could be an important tool for understanding how parts of the community work or
could work together to plan for and respond to disasters. SNA has been used to inform
policy in areas such as terrorism prevention and public health improvement, and could
facilitate decision making related to the improvement of community disaster resilience.
Community resilience, in sociological terms, is the ability of a community or social
unit to withstand external shocks, such as disasters, to its infrastructure. Community re-
silience emerges from a community’s ability to adapt to stress and return to healthy func-
tioning. The speed with which a community can mobilize and use resources during and
following a disaster is strongly dependent on its abilities to adapt to change. The strength
of its social networks is a factor. Building community resilience is a process that devel-
ops the capacities that allow communities to adapt. The building of disaster resilience can
be considered a strategy for disaster readiness. Incremental improvements in resilience
can significantly improve the capacity of a community to prepare for, respond to, and re-
cover from disasters. However, just as a community may change with time, a commu-
nity’s response to a disaster may change with time. A disaster that has little impact on a
community at one time may have a devastating impact on it at another time. An
understanding of the dynamic nature of resilience is essential for good planning.
Successful building of resilience is dependent on the reduction of risk to individuals and
FIGURE S-1 Graphical representation of a social network. SOURCE: Kathleen Carley, Carnegie Mellon
University, Institute for Software Research International (2009).
SUMMARY 5
Workshop participants expert in the field considered SNA theory and applications to
be quite advanced, but participants stated that SNA is not being applied in ways that
assist local communities and practitioners. From the scientific perspective, more and
better data about networks are required for the development of the tools needed to
advance the science and practice of SNA. Additionally, the means to test the validity of
social science models resulting from SNA have yet to be developed. From the
practitioner’s perspective, explanations of SNA and its tools need to be made more
meaningful to gain acceptance in everyday practice. Innovations and a proliferation of
networking technologies (e.g., wireless technologies and networking software) are easily
accessible. Awareness of both the positive and negative issues associated with the use of
networking technologies to support social networking, however, would benefit the
emergency management community.
RESEARCH THEMES
Areas of Research
Baseline Data
Many workshop participants indicated that a certain level of baseline information re-
garding networks is necessary to determine the resilience of a community to extreme
events. Baseline data describe the starting conditions by which change can be measured
and include all manner of data regarding networks and their members. These data are fed
into SNA to produce baseline models. Little, for instance, is presently known about who
populates the formal, governmental networks responsible for a region’s disaster man-
agement or how they may integrate with other social networks that reside in civil society
for emergency management purposes. Without this baseline level of knowledge, it is dif-
ficult to evaluate the evolution of the composition of social networks and how these
changes relate to resilience levels. However, collection and management of baseline data,
Validation Techniques
Mechanisms to validate new data, network models, and decisions made using SNA
and related tools would also benefit practitioners and scientists. Practitioners described
the need for mechanisms that can vet for accuracy the data traveling through a network,
and indicate if the data require action or response. New networking technologies allow
large amounts of data to travel quickly through networks. Practitioners need a means to
sort which data are good, bad, redundant, and actionable.
Networks are likely to change quickly during a disaster as infrastructure fails or is re-
structured, people relocate, or the availability of resources change. Building resiliency
into social networks requires an understanding of how networks evolve during normal
times, and during times of stress. Understanding how networks change when stressed,
and how to promote positive changes that allow the networks to function during a dis-
aster, is important. Some workshop participants suggested that new methods for studying
network dynamics are needed. It is essential that network models be constantly updated.
SNA tools would be more useful to practitioners if they allowed quick visualization of
the changing nature and uncertainties in linkages within and between networks. This
would allow more effective diffusion of information during all stages of the disaster
cycle.
New and more refined data gathering techniques could result in better social network
models. For example, workshop participants repeatedly stressed how SNA could be more
effective if the means of obtaining proprietary and personal data for SNA while preserv-
ing the privacy of individuals and institutions were developed. Such data as who within
and between private sector organizations communicates with whom and what kinds of
people receive certain medical treatment under certain circumstances provide real in-
sights into the nature of networks and their members. Workshop participants stressed the
importance of maintaining privacy. Legal and ethical barriers are an issue.
SUMMARY 7
Study of how SNA is applied in areas such as network centric warfare, counter ter-
rorism, and public health would aid in the application of SNA for improving community
disaster resilience. The vocabulary of network-centric warfare is different from that used
by social scientists, but the goals are similar: to understand and improve how information
is sought and exchanged; and to develop action instruments that enable decision making.
According to workshop participants, practitioners who collect, analyze, understand,
model, and incorporate network data into their decision-making processes may be better
poised to help their communities become more resilient. Building resilience is not only
about preparation for disasters. Studying how networks deal with broader social issues
would also be useful. Research on how communities deal with issues such as ethnic
oppression may yield a rich and pertinent literature on community resilience from which
to draw.
Barriers to SNA research and use of SNA tools by practitioners for building
community disaster resilience were often discussed during the workshop. Although
addressing these barriers is not directly part of the charge given the workshop planning
committee, many participants noted that these barriers could affect the effectiveness of a
future research agenda and the adoption of SNA tools in practice. Suggested strategies to
overcome these barriers are summarized below.
Participants pointed out that current strategies for funding research and moving re-
search results into practice are not adequate to address the large-scale and complex social
science issues. New funding frameworks that accommodate larger and longer-term
studies would benefit both the research and practice communities. For example, better
baseline data from which progress can be benchmarked would probably result. Incentives
to encourage rapid-response investigations immediately following an event, and
multidisciplinary research in general, could lead to more immediately useful results for
practitioners including information on topics such as intervention methodologies that
have proven successful. Collaborative research conducted with practitioners, and between
public and private entities, could make the adoption of SNA techniques among
practitioners more likely. Removing barriers of access to infrastructure and data may also
result. Workshop participants noted that the most relevant research, tools, and data for
decision making would be those identified jointly by researchers and practitioners, with
input received from the private sector.
Some practitioners and researchers at the workshop expressed concern that current
homeland security priorities tend to encourage a focus on antiterrorism activities within
the emergency management community. Some suggested that sources of community
stress need to be adequately assessed to confirm whether a focus on antiterrorism is
locally warranted. A better understanding of community stressors could allow for more
informed allocation of resources.
1
________________________________________________________________________
Introduction
(NRC) to hold a two-day workshop to examine the current state of the art in SNA and its
applicability to the identification, construction, and strengthening of networks within U.S.
communities for the purpose of building community disaster resilience.
To answer its charge, the NRC formed an ad hoc workshop planning committee under
the auspices of the Geographical Sciences Committee of the Board on Earth Sciences and
Resources. The committee was tasked with organizing and conducting the workshop. The
committee’s statement of task is provided in Box 1-1. It includes the identification of
elements of a future research agenda to support the design, development, and implemen-
tation of social networks for the specific purpose of strengthening the resilience of com-
munities against natural and man-made hazards and terrorist events. The workshop took
place February 11-12, 2009, and featured presentations and discussions on social net-
works, social networking tools, SNA theory and tools, and community resilience.
As described by Michael Dunaway of DHS, the ultimate result of a research agenda
influenced by this workshop summary could be the creation of accessible tools that
would enable county-level emergency management directors and other community
leaders to define and visualize networks within their communities. With the ability to
identify relationships within and among networks, social structures and adaptive capaci-
ties can be built and reinforced to make communities more disaster resilient. Workshop
participants discussed whether such tools were possible and the type of research that
could enable their development.
BOX 1-1
Statement of Task
An ad hoc committee will organize a two-day public workshop to examine the current state of
the art in Social Network Analysis (SNA) and its applicability to the identification, construction,
and strengthening of networks within U.S. communities for the purpose of building community
resilience.
The workshop will explore the topic through invited presentations and facilitated discussions
among invited participants, including the following issues:
Current work in SNA that has focused on defining the characteristics, composition, and
structure of existing networks (e.g., terrorist cells; infectious disease transmission;
narcotics trafficking);
Theories, principles, or hypotheses within the science of SNA that could be applied to
the construction of designed networks to develop or enhance the strength of
relationships within geographic or functional communities;
Current research that has focused on the use of SNA for the development of designed
networks;
Gaps in current knowledge within the field of SNA that would inhibit the ability to apply
SNA theories or principles to the construction of networks;
Research areas that could fill gaps in this knowledge; and
Elements of a research agenda that could be pursued to support the design, develop-
ment, and implementation of social networks for the specific purpose of strengthening
the resilience of communities against natural and man-made hazards and terrorist
events.
INTRODUCTION 11
WORKSHOP PLANNING
The workshop planning committee consisted of six members with expertise in the ar-
eas of SNA, spatial social science, hazards, resilience science, and community and disas-
ter management. Appendix A provides biographies of the planning committee members.
The committee held five teleconferences to discuss the statement of task, identify work-
shop participants, and develop an agenda. References shared among the committee mem-
bers became the basis for the bibliography included in the workshop briefing materials
and as Appendix B of this document.
The workshop planning committee selected two major themes around which to or-
ganize the workshop: the use of SNA for preparedness and intervention, and the use of
SNA in improvisational disaster response. The committee invited researchers and emer-
gency management practitioners—those with their “boots on the ground” during an
emergency—to participate. Researchers and community leaders from different geo-
graphical regions of the country, and with varying disaster experiences, were invited so
that a broad range of issues and perspectives could be considered. A list of participants is
presented as Appendix C of this document. Participants included individuals familiar
with SNA for other purposes, such as identification of terrorist cells and for the
development of programs to thwart the spread of infectious disease. Individuals that work
with populations that could be disenfranchised during an emergency, such as the non-
English speaking poor, were included among participants. The workshop agenda appears
in Box 1-2.
The planning committee devoted the first morning of the workshop to defining topics
to be discussed, including community resilience, social networking, and the states of the
science and practice of SNA. Case studies in the use of social networks and SNA were
provided. Summaries of presentations and discussions are found in Chapter 2. As indi-
cated in Box 1-2, the introductory session was followed by concurrent breakout sessions
on the major workshop themes, moderated by a member of the planning committee. The
first set of concurrent sessions addressed how SNA could be used to enhance communi-
cation, and how SNA could be used for planning interventions in preparation for a disas-
ter. The second set of concurrent breakout sessions addressed how SNA might enhance
communications when coordinating the improvisational response of networks of
organizations; and how SNA could enhance communication within local communities
and among individuals. Breakout sessions concluded with a reconvening of workshop
participants to summarize discussions. Appendix D includes descriptions of breakout
session topics as well as questions developed by the workshop planning committee to
guide discussion. Workshop participants were given these descriptions and questions
before the workshop.
A concluding plenary session focused on key gaps in knowledge regarding the ap-
plication of SNA to foster community disaster resilience and the research needed to fill
them. Specific research themes were considered.
This document summarizes the major points and ideas presented at the workshop as
documented by a rapporteur. The summary reflects the specific topics emphasized by
workshop presentations and discussions and may not be a comprehensive summary of all
relevant topics and issues. Any documented observations contained in this summary are
those of individual participants or groups of participants and do not necessarily represent
the consensus of the workshop participants or planning committee, nor does the summary
contain any consensus conclusions or recommendations.
This workshop summary is organized into four chapters. This chapter introduces the
reader to the purpose and organization of the workshop. Chapter 2 summarizes the
introductory presentations and discussions and explores the current states of the science
and practice as presented by workshop speakers. Definitions of key terms used by
workshop participants and in this summary are also provided. Chapter 3 summarizes the
discussions of the utility of SNA in identifying networks and improving community
resiliency before and during a disaster and in the response and recovery phases of a dis-
aster. Chapter 4 synthesizes the ideas of workshop participants on how to move from the
theoretical realm to the practical application of SNA for improving community resilience.
Gaps in knowledge and potential research that could fill those gaps as identified by par-
ticipants are summarized, as are barriers to SNA research and application.
INTRODUCTION 13
BOX 1-2
Applications of Social Network Analysis for Building Community
Disaster Resilience: A Workshop
SESSION 1
INTRODUCTION: TOPIC OVERVIEW AND DEFINITIONS
(PLENARY)
9:05 Discussion
9:40 Discussion
10:30 Discussion
11:05 Discussion
SESSION 2
USING SNA FOR PREPAREDNESS AND INTERVENTION
(CONCURRENT SESSIONS)
Plenary Session
3:45 Reports from Break-out Sessions & Wrap Up
4:30 Adjourn
SESSION 3
IMPROVISATIONAL DISASTER RESPONSE
(CONCURRENT SESSIONS)
Plenary Session
SESSION 4
RESEARCH NEEDS AND IMPLEMENTATION GAPS
(PLENARY)
1:00 p.m. What we don’t know and need to know about SNA and resilience
• Identification of knowledge gaps and priority research areas
• Identification of specific research themes that enhance
implementation of social networks as a means for increasing
community resilience against disasters.
4:30 Adjourn
2
________________________________________________________________________
This chapter summarizes introductory presentations and discussions of the first session
of the workshop. The purpose of the session was to introduce participants to the workshop
charge (see Box 1-1) and the terminology to be used throughout discussions. Speakers
were invited to provide basic information on the sciences and practices of social network
analysis (SNA), fostering community resilience, reaching vulnerable populations through
social networks, and the use of social networking tools to improve communication.
WORKSHOP VOCABULARY
During the first day of workshop discussions, the workshop planning committee
observed inconsistent use of key terms related to social networks and SNA by
participants. To avoid confusion, the committee provided definitions for these terms (see
Box 2-1). A social network is a group of people and organizations that form a web of
relationships. Social networks were being confused with the tools used to facilitate them
(such as Facebook1) or to analyze them. Social network analysis is the process of
analyzing the key actors and connections within a social network. SNA can reveal
redundancies and vulnerabilities within a network, and can be used to study the changes
in all these variables. A product of SNA may be a graphical representation of a network
that shows the interconnectedness of network members. An example is provided as
Figure 2-1.
Issues were also encountered with the use of the term “resiliency.” As described in
Chapter 1, resiliency is the ability of a social unit to withstand external shocks to its
infrastructure (Norris presentation to workshop participants).
1
Facebook is a free-access, privately owned social networking website. See www.facebook.com (accessed
March 24, 2009).
15
BOX 2-1
Definitions of Key Social Network Terms
The workshop planning committee developed the following definitions of key terms used in the
study of social networks and social network analysis.
Social network. The interactions between people and organizations, including who knows, works
with, or communicates with whom, that can be mapped. The data and information found, for
example, in Facebooka and the Enron Email Corpusb are examples of social networks.
Social network tools. A set of computational techniques that enable individuals and groups to
engage in social networking by monitoring and interacting within the networks with which they are
connected. Facebook, MySpace,c and Twitterd are examples of social networking tools.
Social networking. The process of creating, maintaining, or altering one’s network to one’s
advantage by using the network to gain resources or influence, or to mobilize activity.
Social network analysis. The process of analyzing a social network and identifying key actors,
groups, vulnerabilities, and redundancies as well as the changes in these variables.
Social network analysis tools. The set of tools, technologies, metrics, models, and visualization
techniques used for social network analysis. These may include data extraction tools, link
analysis, statistical techniques, and graph theory techniques using programs such as AutoMap,e
ORA,f UCINET,g and Pajek.h
Social network theory. The set of theories for forecasting, reasoning about, and understanding
how social networks form, are maintained, and evolve, and the role of variables such as social
networking tools, media, and stress in affecting the emergence, utilization, management, and
change in social networks.
a
See www.facebook.com (accessed March 2, 2009).
b
See, for example, ebiquity.umbc.edu/blogger/2006/02/05/search-the-enron-email-corpus-online/ (accessed
March 2, 2009).
c
See www.myspace.com (accessed April 5, 2009).
d
See twitter.com/ (accessed March 2, 2009).
e
See www.casos.cs.cmu.edu/projects/automap/ (accessed May 10, 2009).
f
See www.casos.cs.cmu.edu/projects/ora/ (accessed May 10, 2009).
g
See www.analytictech.com/downloaduc6.htm (accessed May 10, 2009).
h
See vlado.fmf.uni-lj.si/pub/networks/pajek/ (accessed May 10, 2009)
FIGURE 2-1 Graphical representation of a social network. SOURCE: Kathleen Carley, Carnegie Mellon
University, Institute for Software Research International (2009).
Kathleen M. Carley of the Center for Computational Analysis of Social and Organization
Systems (CASOS) of the Carnegie Mellon Institute was invited to give a presentation on
the state of the art in SNA. She provided an overview of the main tools of SNA that focus
on defining the characteristics, composition, and structure of existing social networks.
Her presentation and subsequent discussion are summarized here. Other topics and issues
may be relevant to SNA, such as the study of ego networks, but were not discussed at the
workshop and not included in this summary. Unless otherwise noted, the ideas expressed
in the following sections are attributable to Dr. Carley.
People, units of action, partners, departments, resources, ideas, skills, events, and
countries can be graphically represented as nodes in a network (for example, the dots in
Figure 2-1). The links—or ties—between the nodes are the interrelations and may
represent physical ties such as roads or rivers, or less tangible ties such as alliances,
associations, authority lines, transfer of resources, precedence, or who likes or respects
whom. SNA can be used to identify and understand the relationships and strengths of the
ties within a network, and understand how these ties are vulnerable under certain
circumstances. SNA can also be used to conduct sentiment analyses to understand the
flow of ideas or feelings.
Classic social network and link analysis modeling and basic pattern detection
capabilities are readily available but not commonly applied in policy making.
Nonetheless research in SNA is rapidly expanding and cutting-edge technologies yield
exciting results with sociopolitical ramifications. SNA is mostly unused at the local level
with the exception of epidemiological studies, such as the tracking of disease sources,
Traditional SNA focuses on nodes within a network and considers the attributes that
make an individual node stand out. The state of the art in the field of SNA is beyond
determining who communicates with whom. Newer approaches to SNA consider
networks as a whole, and powerful techniques exist that allow the analyses of the what,
where, how, why, and when of situations. These techniques enable a user to identify the
need for interventions, plan for them, and provide input for policy management. Most
agencies, including disaster management agencies, currently collect “trail data,” such as
who entered a health department on what day for what information, or who crossed the
border at what time.
State-of-the-art data collection includes a dynamic network analysis suite of three
types of tools to track and analyze trail and other network data. The suite includes (1)
data mining tools, such as AutoMap, that collect network data from open sources such as
newspapers to identify network components; (2) statistical analysis-type packages, such
as Organizational Risk Analyzer (ORA), that take into account social and dynamic
network metrics, conduct broader data mining and link analyses, and apply machine
learning techniques for clustering; and (3) simulation tools, such as DyNet, Construct,
and BioWar, that allow scenario analysis for the consideration of various options. Box 2-
2 provides descriptions of some of these tools.
Although dynamic social network analysis is used in some applications, many
barriers exist to their widespread use for analyzing complex networks. It is difficult to
extract text and links from the wide range of required data sources. Many applicable
analytical techniques for city-scale networks require extensive computational resources.
Additionally, many simulation models are built for a single purpose and cannot be
reused, quickly making them obsolete. Finally, interpreting and moving this level of
information into the policy realm and scale is not yet a functional reality.
BOX 2-2
Dynamic Network Analysis Tools
AutoMap is a product of CASOS at the Carnegie Mellon University and is a text mining tool that
enables the extraction of network data from texts. The tool can extract content analytic data
(words and frequencies), semantic networks, and metanetworks. The main functions of AutoMap
are to extract, analyze, and compare mental models of individuals and groups, and to reveal the
structure of social and organizational systems from texts.
SOURCE: www.casos.cs.cmu.edu/projects/automap/ (accessed March 21, 2009).
BioWar is a CASOS package that enables community leaders to prepare for biological attacks
using computational models of social networks, communication media, disease models,
demographically accurate agent modes, wind dispersion models, and a diagnostic error model
combined into a single model of the impact of an attack on a city.
SOURCE: www.casos.cs.cmu.edu/projects/biowar/ (accessed March 21, 2009).
DyNet is a reasoning support tool developed by CASOS intended to simulate reasoning about
dynamic networked organizations under varying levels of uncertainty using computer science,
social network, and organization theory.
SOURCE: www.casos.cs.cmu.edu/projects/DyNet/dynet_info.html (accessed March 21, 2009).
i2 Analyst’s Notebook is a commercial visual investigative analysis tool that allows investigators
to organize large volumes of disparate data and conduct link and timeline analyses.
SOURCE: www.i2inc.com/products/analysts_notebook/ (accessed May 12, 2009).
Organizational Risk Analyzer (ORA) is a risk assessment tool developed by CASOS that
examines network information and identifies individuals or groups that are potential risks to a
network given social, knowledge, and task network information.
SOURCE: www.casos.cs.cmu.edu/projects/ora/ (accessed May 12, 2009).
Palantir is a commercially available information analysis platform for integrating, visualizing, and
analyzing structured, unstructured, relational, temporal, and geospatial data for security,
intelligence, defense, and financial applications.
SOURCE: www.palantirtech.com/ (accessed May 12, 2009).
R is a computer language and environment for statistical computing and graphics developed by
Bell Laboratories. SOURCE: www.r-project.org/ (accessed May 12, 2009).
UCINET is a commercially available comprehensive package for the analysis of social network
data using a variety of network and statistical analysis methods.
SOURCE: www.analytictech.com/ucinet6/ucinet.htm (accessed May 12, 2009).
Available tools make it possible to conduct network analysis with open-source, raw-
text data input, such as information from newspapers, and then conduct scenario analysis
(e.g., what would happen given a certain set of circumstances), and finally conduct
analysis that can identify emergent leaders. Analysis is possible, for example, that can
connect all of the potential emergency responses in a community to specific emergency
responders in order to see where vulnerabilities in a response network exist. Location
analysis can be done to see how things are done differently in different areas. Geospatial
network analysis is possible, as is information gain and loss tracking. It is also possible to
detect changes in organizations and behavior over time within a network using available
analytical techniques. If the resources are available, the mapping of belief structures and
trends over time is possible and may allow policy makers to identify where people hold
certain beliefs, where beliefs are likely to change, who the critical actors are that enable
change, and to predict who will be central to the network in the future. Belief forecasting
analysis can be conducted for given types of network structures and sociodemographics.
The results of the analysis provide policy makers and leaders with powerful information
to help them determine how best to communicate with and enlist the assistance of their
communities.
The resulting data and models from dynamic social network analyses can allow
managers to identify critical network features, identify opportunities for intervention
analysis or action, and conduct limited types of event forecasting.
Framework modeling and network statistical analysis tools are readily available to
community and disaster managers, but those using them often are not familiar with com-
munity social science models. Under such circumstances, statistical analyses may be
overapplied, good interpretation of network situations may be missing, and resulting
models may be in error. Even scientifically sound network models may be used incor-
rectly, or metrics for change may be misinterpreted. According to some workshop par-
ticipants, increased communication between social scientists in the research community
and modelers within emergency management communities would be beneficial. A barrier
to collaboration, however, is that researchers and practitioners do not use the same
analysis tools. Different tools are used, in part because of the cost and accreditation of
software, and because of the scalability and visualization capabilities of various software
packages.
To realize the benefits of SNA, it is essential that information move from the research
realm into practice, also known as translation of research. Research conducted on the best
means to translate information is defined as translation research. Translation research can
be helpful in developing an educational process that demonstrates how the adoption of
new ideas and tools will yield actionable results for practitioners. Methodologies,
language, and examples that would be most meaningful to a target audience can be
identified. Louise Comfort of the Graduate School of Public and International Affairs,
University of Pittsburgh, described experiences promoting the use of networking
technologies in different municipalities. She found that new technologies could be
quickly accepted if individuals were willing to think beyond their traditional routines
(Comfort and Wukich, 2009). She described the interaction and process of learning that
occurs on at least three levels to create a learning network:
Generally, younger personnel with access to better equipment were more willing to
accept new technologies. Acceptance of technologies into practical use has occurred
within the drug-traffic enforcement and healthcare communities. Acceptance more often
occurs when champions of the technologies are identified within the communities to
collaborate in the development of educational materials. Similar relationships would be
useful to the disaster management community.
Translational activities validate basic findings for practitioners in language that can
be understood, and can result in the decrease in the time to move a concept from the
research realm into practice. Dr. Carley indicated that the engineering field engages in
translational research that results in a relatively small lag of six years between the
inception of an idea and its practical application. She stated that the translation of
complex SNA techniques is estimated to occur only after approximately 24 years because
the SNA community is not actively engaged in translational research and activities.
Without translation research, widespread benefits resulting from the application of SNA
will be negligible. In spite of this, no agency is charged with funding such research.
Cost
resilience. It was discussed during the workshop that a complex network analysis for a
system at the city level could require between half a million and several million dollars.
The cost can vary significantly depending on the data already available and the level and
condition of available hardware. The cost of SNA tools may be controlled by taking
advantage of free and currently available state-of-the-art tools. Agencies typically use
commercially available software at a cost of thousands of dollars.
Validation of Models
Behavioral Factors
Not enough is currently understood about how trust in and reliance on information
sources change as a result of stress. A better understanding of the nature of these changes
in a technology environment could allow these concepts to be usefully incorporated into
network models and decision making. Additionally, researchers may understand how data
are collected off the Web and how individuals use their networks, but it might not be
understood how the flow of information changes if the status of individuals’ connectivity
to the Web changes. Researchers do not know, for example, how Internet penetration in a
network changes who the opinion leaders of a network are. This gap is acknowledged and
being addressed by the Office of the Secretary of Defense.
Fran H. Norris of the National Center for Disaster Mental Health Research of the
Dartmouth Medical Center was invited to define community resiliency in a presentation
to workshop participants. This section summarizes her presentation in combination with
the discussion it generated. Unless otherwise noted, conclusions may be attributed to Dr.
Norris.
What is Resilience?
Resilience is one of multiple possible stress responses to a disaster that also include
resistance, recovery, and chronic dysfunction. Communities resistant to a specific event
are barely affected by it. A resilient community may display transient dysfunction that is
quickly resolved following an event. For some communities, dysfunction is more slowly
resolved, but the community ultimately recovers. Chronic dysfunction represents the
failure to adapt to the new circumstances. Factors controlling response trajectories are
severity of exposure, the existence (or the perception of the existence) of social supports,
and social class.
Different levels of distress can be observed within a single community following a
disaster, as demonstrated in a case study of mudslide victims in Mexico in 1999. A high
degree of property damage, bereavement, and complete displacement was observed
following mudslides that destroyed a large portion of a community. Levels of distress,
such as symptoms of post-traumatic stress disorder, were monitored among the
population over time. Approximately one-third of the community was resistant to stress
and was observed to have few symptoms. Another third of the community showed very
high initial distress that improved at different rates. This group displayed different levels
of resiliency but eventually returned to normal function. The remainder of the population
showed moderate and high levels of distress that did not improve over a 24-month period.
This group was considered chronically dysfunctional.
The social capital available to the community through its networks, including
organizational linkages within a community, the amount of social embeddedness,
the attachment to place, the sense of community, citizen participation, and the real
and perceived support in the face of adversity;
Balanced levels of social capital, community competence, and ability to access and
communicate information build resilience by enabling those qualities that help a
community function as a community in the face of adversity. Economic development—
including the level and diversity of economic resources, the equity of resource
distribution, and the fairness of distribution of risk and vulnerability to hazards—is also
important in building resilience.
Significant improvements in community resilience could result using the public
health approach of encouraging small shifts in population response to disaster events.
Figure 2-2a shows the distribution of the common response trajectories of victims of the
Mexican landslide case study described earlier. Figure 2-2b shows what the responses in
the same population could be if only 5 percent of the total population could be made
more resistant, 5 percent could be made more resilient, and 5 percent of those who would
not have recovered could be assisted into recovery. Such improvements can be achieved
by intervening at multiple points, and addressing multiple adaptive capacities, before and
during a disaster, and again later in time. Such improvements may include
The means to measure adaptive capacities, especially in the area of communication, have
not been developed. SNA may provide a reasonable means of measuring the adaptive
capacities associated with community resilience and in determining how best to intervene
to achieve the desired improvements.
Chronic
Chronic dysfunction
dysfunction
Recovery 7%
22% Resistance
35% 16%
40% Resistance
Recovery 11%
32% 37%
Resilience
Resilience
FIGURE 2-2 Distribution of response over a 24-month period by a population impacted by Mexican
mudslides in 1999. 2-2a represents observed responses. 2-2b represents the potential response given a
positive shift of 5 percent in both the resistant and resilient groups, and in those able to recover in the
longer term. Note the percentage of the population that remained chronically dysfunctional would be
dramatically reduced with the application of this public health approach. SOURCE: Fran Norris,
Dartmouth, workshop PowerPoint presentation.
The workshop planning committee sought to explore how social networks and SNA
could be used to reach vulnerable populations that may become disenfranchised from the
larger community following a disaster. Because of the limited number of case studies on
this topic, the committee looked to a case study from the public health community. Carl
Latkin of the Johns Hopkins Bloomberg School of Public Health was asked to give a
presentation on his efforts to recruit inner-city residents at high risk for HIV infection and
transmission to promote positive behaviors within their communities. His presentation
was related to how social and personal network approaches were used to both create
networks among vulnerable populations and potentially influence behaviors within the
networks. In the social network of impoverished inner-city populations, a high degree of
network linkages exist among impoverished individuals and individuals with chronic
physical illnesses, mental illnesses, and drug addiction. Consequently, social network
analyses afford a viable approach to reaching these vulnerable populations.
A summary of Dr. Latkin’s presentation and ensuing discussion are provided here.
Conclusions presented are by Dr. Latkin unless otherwise noted.
Insufficient service capacity exists to deal with the demands of daily medical
emergencies in many major northeast urban cities. Emergency Medical Services (EMS)
may be overwhelmed by nonemergency uses by substance abusers, the mentally ill, those
in nursing homes, and the homeless. The design of social service networks discourages
use of public resources by forcing people to wait in long lines, by treating them poorly,
and encouraging distrust between service providers and impoverished populations.
Building successful networks and services is dependent on building trust, an important
adaptive capacity. Interacting with EMS or the fire department is a good way to see the
conditions, plights, and social isolation before developing interventions.
The Johns Hopkins Bloomberg School of Public Health used network approaches to
reach highly impoverished individuals and change unhealthy behaviors. Inner-city
residents at high risk for HIV infection and transmission were recruited in Philadelphia,
Pennsylvania, and in Thailand to promote risk reducing behaviors in their communities
(Latkin et al., 2009). Systematic study of and establishment of rapport with the
communities were necessary to gain the trust vital to the success of the programs. The
nature and stability of needle-sharing networks over time were studied. Networks
consisted of up to 10 individuals who shared needles and sex. Some network stability
existed, but a fair amount of fluidity and turnover of individuals were observed. Some
linkages of these smaller individual networks to a larger social network were noted, but
not all members of the community were linked.
Introducing Interventions
Individuals with a desirable combination of skills and natural leadership abilities were
enlisted from over 400 of the needle-sharing networks to educate their peers. They were
18 years or older, had weekly contact with active drug users, and were willing to be
trained to conduct outreach education and bring network members into the program. The
identified leaders were paid to receive training, but received only symbolic rewards for
talking to their friends, modeling risk reduction behaviors, and socially influencing the
critical behaviors that prevent HIV infection. Given the high level of stressors and
traumas within these populations, redundancies were incorporated into the networks
because of the likelihood a leader would become unavailable. Control groups were
established to measure the effectiveness of information diffusion and the potential of
behavioral changes.
Over a thousand community members participated in the intervention that consisted
of six small-group peer-educator training sessions. After 24 months, participating
network members were up to twice as likely to have reported not engaging in high-risk
injection behaviors. These individuals were also more likely to have engaged in
conversations regarding HIV risk behaviors following the training. The efficacy in
reducing risk was not established in the studies.
The case studies presented here describe intervention efforts targeting small networks
whose members may not be attached to larger community networks. Workshop
participants discussed that the stability of these networks is fragile at best, and
disintegration of the networks is likely following a disaster. Individuals within these
communities are at severe risk of being further disenfranchised from the larger
community, and may lack any knowledge of, access to, or trust in aid offered in response
to a disaster.
Workshop participants expressed a need to consider how communication with all
members of a community, including individuals within disenfranchised or potentially
disenfranchised populations, should occur. The means to communicate and provide
services to all community members during each phase of the disaster cycle is essential.
Special study of the means to build disaster resilience among fragile communities, such
as those described by Dr. Latkin, is desirable.
It is important to go into communities to understand the access, feasibility, and
reliability of resources, and to understand how many people are reliant on the same
resources. This is especially true in disaster management settings when many people may
depend on the same resources, or the availability of the resources may change. Social
network analyses afford a viable approach to reaching these vulnerable populations.
In the last decade, numerous digital networking tools have been developed that are
changing the way many in American culture communicate. The workshop planning
committee invited Michael Byrne of ICF International Inc. to provide background on
these tools and relate how emergency managers could use them during all phases of a
disaster. This section summarizes his presentation, entitled “Impact of Technology on
Collaborative Homeland Security: Web 2.0, 3.0, 4.0 and Beyond,” and the discussion that
followed. Many of the experiences relayed were anecdotal but are descriptive of the
issues and solutions at hand.
A new vision for the Internet began to take shape during the Web 2.0 Conference in
2004.3 Web 2.0 represents a culture shift, with the Internet being controlled by users from
the bottom and providing an interactive environment that fosters innovation. Users
become active participants rather than observers. The Internet now offers rich user
experiences including Web video, interactive maps, timely content, and virtual worlds4
which can be used not only for online entertainment but also for practical purposes such
as conferencing and training. The evolution of the Internet will continue beyond Web 2.0
with the development of tools such as autonomous intelligent agents that are programmed
to recognize user interests and filter and manipulate information the user sees. This is
already being applied to some extent to target advertisements to Internet users.
As defined in Box 2-1, social networking tools enable individuals and groups to
engage in social networking by monitoring and interacting within their networks. Text
3
A conference held by O’Reilly Media Inc. and MediaLive International (www.web2con.com/web2con
[accessed April 5, 2009]).
4
Virtual worlds are computer-based simulated environments in which single or multiple users can
communicate and manipulate events within the environment.
and multimedia information can be easily shared using relatively inexpensive and
accessible technologies and distribution networks available for free on the Internet.
According to Mr. Byrne, 3.75 billion people in the world have mobile communication
devices. Sixty-two percent of all Americans have experience accessing wireless digital
data and tools (Horrigan, 2008). Emergency managers who do not use these tools to reach
their communities, build networks, and improve communication risk the possible
detriment of their communities.
Twitter allows members to distribute text messages, called “tweets,” of up to 140-
character with their cell phones to geographically-, group-, or friend-based networks.
According to the website TechCrunch,5 information regarding the 2008 terrorist attacks
in Mumbai was shared worldwide in quasi-real-time using Twitter—faster than news
agencies such as CNN reported the events. In London, 62,000 cameras record much that
occurs in public spaces. Communities in England are networked, and video information
of interest can be shared in real-time. Individuals anywhere in the world can share visual
information over networks using tools such as Flickr6 and YouTube.7
The emergency management community has largely missed the networking
revolution. Emergency management practitioners would benefit from a new
communication paradigm and from studying how others are using social networking
tools. For example, the Department of Health and Human Services has used the virtual
world Second Life to run training drills;8 law enforcement agencies have used gaming
technologies for “shoot, don’t shoot” drills; and America’s Army9 uses gaming
technologies to teach basic first-aid skills. This type of training could prove to be an
inexpensive alternative to traditional training approaches.
Workshop participants heard anecdotal evidence that evacuated New Orleans city
staff used social networking tools to organize and get things done following Hurricane
Katrina. This was possible in spite of individuals being spread geographically, and far
from New Orleans. The electronic convergence of people into widespread information
networks can enhance the concept of resiliency in a global sense.
Digital Divides
5
See www.techcrunch.com/2008/11/26/first-hand-accounts-of-terrorist-attacks-in-india-on-twitter (accessed
April 3, 2009).
6
Flickr is a Web-based photo management and sharing tool (see www.flickr.com [accessed April 3, 2009]).
7
YouTube is a video sharing website where users can upload, share, and view video clips (see
www.youtube.com [accessed April 4, 2009]).
8
See secondlife.com (accessed April 5, 2009).
9
See www.americasarmy.com (accessed April 5, 2009).
use or have access to social networking tools. It is still essential to conduct door-to-door
searches following an emergency in spite of great advances in networking technologies.
A digital divide also exists between many government entities and the public. Many
organizations prohibit access to Internet sites such as Facebook and MySpace.10 The
organizations have not kept up with networking technologies or have not used them ad-
vantageously to communicate with constituents. Government agencies will be unable to
ignore networking tools because of the growing reliance on networking (versus
traditional communication approaches) by the public. Many municipalities resist the
adoption of networking tools because of valid or perceived security concerns. Agencies at
all levels often opt to take control of security issues by creating their own networking
tools—an expensive approach that could result in quickly outdated technologies.
However, some government agencies are now exploring and even embracing the active
use of social networking tools.
Double-Edged Sword
Even though networking tools can be successfully used to spread information, Mr.
Byrne also sees them as a double-edged sword. Information may not be well managed,
systems may be overwhelmed by a large number of messages, it is difficult to prevent the
spread of misinformation, and infrastructure can fail during catastrophic events. High-
tech solutions need to be balanced with lower-tech solutions to ensure that redundancies
and backups exist. Network tools are easily used by those with both honest and dishonest
intent. Workshop participants learned how some terrorist organizations are known to use
tools such as Twitter and Google Earth11 to update their networks. The challenge for the
emergency management practitioner is to synthesize and analyze the large volume of
information available and determine whether the information is correct, actionable, or
requires response.
Some believe that a large group of people sharing information can arrive at more
accurate conclusions than a small group of experts discussing a given topic (Surowiecki,
2004). Many believe this is the strength of the Internet. Interactive connectivity implies
constant feedback that makes a system self-correcting. As of 2007, there were over 60
million blogs12 on the Internet (Wyld, 2007). Sites such as YouTube and Facebook create
a value beyond what a top-down control model provides. However, bottom-up
organizations largely shaped by its members can be disorganized, loosely controlled,
unmethodical, and sometimes inconsistent, in part because they are in constant states of
flux. Conflicting information may make it difficult to determine which information
sources are accurate, and bad information may promote unwanted behaviors. Charles
Mackay wrote a book in 1841 entitled Extraordinary Popular Delusions and the Madness
of Crowds in which he discusses the perils of the spread of misinformation. The high
10
See www.myspace.com (accessed July 16, 2009).
11
Google Earth is a virtual on-line globe with free downloadable drivers that displays satellite images of the
earth’s surface at different resolutions. Users can add their own data and overlay their own images (see
earth.google.com/index.html [accessed April 3, 2009]).
12
A blog is a user-generated and regularly updated online journal. An example blog mentioned by Michael
Byrne is Disaster Zone: EmergencyManagement in the Blogosphere, maintained by Eric Holdeman (see
www.disaster-zone.com [accessed April 3, 2009]).
level of connectivity in society today creates the potential for major disasters or
magnification of disasters through the unintentional or intentional misuse of networking
tools.
Bad information can be long-lived on the Internet and can persist even on successful
social institutions such as Wikipedia,13 where entries are subject to constant review by
members. Even considering content error, these institutions remain successful because
within their bottom-up organizational structures, ways are available to manage data, look
for and fix problems, and recognize and resolve attacks on the system.
For application in the disaster management community, it is essential that systems
and networks are functioning before a disaster in order for them to be effective during
and following a disaster. The physical infrastructure required to operate the networks
may be resilient, but infrastructure failure is possible during a catastrophic event. In this
situation it is essential to assess the needs of the impacted community and to
communicate to people outside the affected area about the contributions they can make. It
is also essential that the physical infrastructure be restored.
Workshop participants pointed out that emergency response plans generally call only
for restoration of communication infrastructure among response agencies, and no author-
ity exists among emergency managers to restore communication and networks used by
the public. However, current networking technologies allow the quick localized re-
emergence of networks wherever a transmitting device is functioning. Some management
of network re-emergence would benefit emergency managers. Partnerships among public
and private entities could provide solutions.
Shifting Paradigms
innovations at different social and management levels to identify and close disconnects
between those that need resources and those that have access to them would be
beneficial. Networking tools can be intelligently used to engage meaningfully with the
community to positively influence behaviors, influence mitigation and preparedness
strategies, build more resilient systems, and improve response and interventions.
3 3
________________________________________________________________________
33
Session 2a participants (see workshop agenda, Box 1-2) identified three inter-related
long-term goals for improving communication for disaster preparedness and intervention:
Tools are currently available to accomplish some of these objectives, and new
technologies are rapidly evolving. However, many existing tools may be too
academically oriented for practical application or are not packaged for the specific needs
of the disaster management community. The most effective user interfaces for computer
programs could be developed with the full cooperation of emergency management
practitioners and an understanding of the practitioners’ needs. Workshop participants
noted that to get the most out of networking tools, practitioners will need training in their
use. Interpretation of network visualization graphs (Figure 2-1, for example) will need to
be incorporated into the training of law enforcement and first responders. Training in the
use of networking tools would also be essential at the community level to educate the
public on topics such as how to send text messages, and how to communicate with family
members during emergency events.
The next three sections of this document discuss in greater detail the three objectives
stated above.
Many workshop participants stated that a network planning and visualization tool for
the emergency management practitioner cannot be designed to perfectly plan for every
disaster or reach every individual in a community. However, such a tool could be
invaluable in helping managers maximize connectivity within networks and building
community disaster resilience.
Building the tool could be accomplished in phases. Initial phases could allow basic
SNA functions as described in Chapter 2. Emerging technologies, such as data mining
and different analysis techniques, could be incorporated into future phases. The goal of
the primary phase could be to provide planning support for the Department of Homeland
Security (DHS), community leaders, and other community groups. Initial challenges will
likely be indentifying the capabilities the tool should have, identifying aspects of
networks that need to be targeted, getting data into the tool, and developing the capacity
to maintain and update the data. Workshop participants stated that for planning purposes,
the tools would give practitioners an understanding of a community’s adaptive capacities
during different emergencies. Sufficient flexibility to accommodate dynamic networks
and technologies would make the tool more useful.
Workshop participants considered lessons learned from organization theory research.
Optimizing a network could reduce the adaptability of that network; for example,
optimizing a network to increase the speed with which goods are delivered during
nonemergencies may involve choosing specific resources and transportation modes.
Without backup plans and flexibility during times of crisis, people may be put at risk if
the goods are unavailable from regular sources, or infrastructure fails. If the goal is to
increase resiliency, it is essential that the network’s adaptive capacities—its abilities to
function under stress—are encouraged to expand and remain flexible. Given this
information, workshop participants discussed incorporating network optimization
functions into planning and visualization tools only with proper caution so as not to limit
flexibility.
On the infrastructure side of the issue, the means of managing bandwidths required
for social networking is challenging. Understanding the impact of the use of various
cyber-enabled communication tools during a disaster situation is a new endeavor, and
difficulties encountered when encouraging the public to use the communication channels
designated by emergency managers is exacerbated during disaster situations. Theory
building and data analyses in these areas would also be beneficial.
The third of the long-term communication goals described earlier is the development
of tools to conduct impact and scenario analyses. The tools could include those that (1)
explore the best ways to disseminate negative news without making a bad situation worse
(for example, what happens in a network if a specific warning is sent to a specific media
outlet); and (2) choose the best of several options given a specific scenario (for example,
what happens if electricity is restored first to one location rather than another). Tools that
allow the user to understand the impact of information and actions were considered
useful by workshop participants, but their use is largely dependent on an understanding of
networking theory.
Workshop participants noted that the need for tools for impact and scenario analyses
is not unique to disaster management. Commercial tools are under development for
marketing purposes, and the Department of Defense is developing tools for security
purposes. Multiple private sector organizations are exploring tracking capabilities using
text mining and text analysis techniques. Quickly and visually tracking the rapid changes
that occur during an emergency is challenging, especially when changes are monitored
over a variety of media.
Workshop participants observed that quality data are required to conduct SNA
analysis, and that such data are often unavailable. The lack of data and the capacity to
manage large datasets are impediments to the use of SNA for real-time applications. In
some cases, data exist to populate SNA tools, but there may be legal issues regarding the
use of private information by public entities, or reluctance among jurisdictions and
organizations to share data. The use of networking tools, as noted by workshop
participants, is also somewhat incompatible with the DHS National Incident Management
System (NIMS) guidelines for managing domestic incidents.1
Quality baseline data were also considered essential to effective SNA. The current
state of a community has to be understood before effective interventions can be optimally
designed and implemented, and their impacts measured. However, some workshop
participants stated that the cost of collecting baseline data through interviews, fieldwork,
and other means is prohibitive.
1
The DHS issued and revised the National Incident Management System (NIMS) to serve as a template to
manage incidents of any size regardless of the cause, location, or complexity. See
www.fema.gov/emergency/nims/index.shtm (accessed April 20, 2009).
The cost of developing and maintaining new technologies is also high. Champions of
networking technologies within communities and in Washington, D.C. (where they could
interact with the federal government or appropriate interest groups) could be identified
and asked to encourage the development and use of network planning and analysis tools.
The most effective champions would be able to communicate the utility of networking
and analysis tools to people such as first responders and those empowered within the
community to overcome political obstacles. Partnering with groups that are already
developing tools for impact and scenario analyses may be an effective means of
advancing their development and use for emergency management purposes. Including
emergency management practitioners in all stages of the conversation regarding the
promotion of networking technologies would likely yield the most promising results.
Participants of Session 2b (see workshop agenda, Box 1-2) discussed three main
issues:
Workshop participants shared examples of how some practitioners and policy makers
have at least a rudimentary understanding of social networks. Local communities in
Southern California, for instance, have tapped into existing social networks to
disseminate preparedness information. Lay health educators from the Latino community
use their existing social networks to distribute information on earthquake preparedness
and to share coping strategies across communities. American Red Cross staff are seeking
to build organizational linkages with business partners, creating a more robust network of
people able to staff emergency shelters. SNA is being incorporated to some degree in
models to measure the effectiveness of epidemic disease containment measures in the
case of pandemic influenza.
Practitioners and researchers alike raised numerous questions regarding the integra-
tion of social networking and SNA into management policy and practice. According to
some workshop participants, the research literature already answers some of these ques-
tions, but primary research is still needed on a variety of topics and scales related to dis-
aster management agency responsibilities, community networks, and the interactions
between them. For example, does being prepared for disaster within one network (e.g.,
where an individual is employed) make an individual more prepared in another network
(e.g., at home or within a religious community)? The effectiveness of using networks to
promote resilience, disaster readiness, response, and recovery at different levels of soci-
ety down to the household level could be studied. The identification and roles of faith-
and community-based organizations within a community need to be explored. Compara-
tive studies on the ways social networks affect levels of community resilience in diverse
places such as Israel, the United Kingdom, and Japan would help build understanding of
the network characteristics that are successful in this context.
Several questions were raised by workshop participants regarding the role of
organizational culture (for example, fire, police, emergency medical services, and public
health departments) in building social networks, in the sharing of information in the
disaster context, and in building resilience in general. Research on the ideal network
among these groups and the role of technology in facilitating it could provide the
guidance needed to create the robust and flexible networks that are sustainable during a
disaster. Research on networks that cut across districts or local, state, and federal levels
of government and disaster management goals could lead to study of how these networks
could be improved.
Emergency management practitioners would benefit from understanding the
difference between information and resource networks, as well as the implications of
those differences, so that they may effectively use networks to plan and implement
interventions. Understanding how to identify and communicate with the correct people
and organizations within different types of networks would also be useful. Research on
the characteristics and behaviors of groups that are effective at organizing themselves for
action around the hazards in their communities could inform practitioners about which
community behaviors are advantageous and which are not. Similarly, research on how
emergent groups use social networking technologies, for what purposes, and how these
activities could be improved would also be important.
Several workshop participants observed that the research infrastructure does not
support the longitudinal research necessary to understand and apply SNA for building
community resilience. A substantial infusion of research support would be essential to
develop and maintain both longitudinal and rapid-response research. Workshop
participants discussed the idea of creating regional collaboratives of local universities,
agencies, and businesses. These collaboratives could be funded with local, state, and
federal resources, and could serve as repositories for regional baseline data. Their
existence could encourage thorough baseline expertise on regional social networks and
adaptive capacities, and they could be information resources for federal and local
response agencies during times of crisis. The regions could be consistent with the 10
regions into which the United States is divided by FEMA. Both longitudinal and rapid-
response research could be conducted within the framework of the collaboratives.
In thinking about how organizations work together during a disaster, the participants
of Session 3a (see workshop agenda, Box 1-2) considered improvisation an important
aspect of disaster response. SNA has the potential to reveal new ways to coordinate or
influence the convergence of people, resources, and information to improve
improvisational response—those activities planned in immediate response to changed
conditions or resources. Different organizations (e.g., police, public utilities) are
responsible for different aspects of response, and all benefit from knowing what the
others are doing. An organization or individual that responds in unexpected ways outside
the organizational mission context can be like a musician playing a sour note; discord can
be the result. Questions arise regarding how to involve individuals and groups in the
response process; who is responsible for doing so; and how is information about their
involvement shared among networks. The data essential for making these decisions are
often unavailable.
The next sections of this chapter summarize workshop discussion of how networks of
networks may be used to foster improvisational response, communication, and resilience.
SNA is a useful tool for understanding the nonlinear nature of many ties within
networks and organizations. It may also help identify how flexibility could be built into
networks and organizations to allow for effective planning given uncertain
circumstances. Practitioners are most successful working with teams that continue to
function sustainably during the unexpected. Of importance to the practitioner is how to
create ties with those groups with interests relevant to a particular problem. For example,
developing ties with animal rights groups may be beneficial when dealing with problems
associated with the increased number of stray animals following a disaster. Better ties
with a large number of organizations will likely yield greater network resiliency during
times of disaster. A greater probability of successful and timelier response and recovery
may also result.
Baseline data help researchers understand the conditions necessary for building
successful relationships to achieve desired outcomes. Because disasters are not contained
within jurisdictional or geographical boundaries, building ties and brokering information
across agencies and jurisdictions could prove effective. The knowledge base is increased
and additional resilience is built into the combined networks. Baseline data and SNA may
also help emergency practitioners determine the needed balance between efficiency and
redundancy when developing relationships for resilient networks. Establishing
redundancy in a network requires resources, but is essential in situations when a part of
the network fails. Some workshop participants cautioned that redundancy that creates
competiveness among network members should be avoided.
Sustainable ties can be built with interfaces between government and community-
based networks. Traditionally, communication during a disaster has been one-way, from
emergency management to the public. Many workshop participants predicted that two-way
communication will be central to future disaster responses. The practitioner will be most
effective by staying informed of the dynamic nature of relationships within a network and
how these relationships may change day to day and in response to stress. This is essential
to sustainable communication within the network. Technologies available today can
already provide practitioners with many pieces of information that when combined, tell a
story of what a network is doing and how it may be changing. Practitioners can use cell
phones to monitor movement and receive status updates from the emergency
management community or the public using networking tools, such as Twitter, to stay
informed. SNA research conducted to determine how best to monitor constantly changing
and emerging networks would aid practitioners. Avoiding infringement of privacy rights
would be an aspect of this research.
Workshop participants discussed the critical need for baseline research to understand
how a community and its networks function normally and under stress. Some functioning
may be chaotic and emergency managers could benefit from understanding when chaos
does not need to be controlled. Some chaos may appear in the form of ad hoc groups that
spontaneously offer assistance. Effectively working with these groups without a plan or
knowledge of their capabilities depends on the ability of practitioners to direct volunteer
response efforts appropriately. Impromptu enthusiasm can be harmful if not controlled.
For example, the delivery of unneeded supplies could create added burden for emergency
managers and distract them from more essential responsibilities. SNA may help
determine where volunteer group efforts can be used. Research on how to foster the
ability to rely more on improvisational response could be useful. According to workshop
participants, determining who will direct these groups is as important as how to direct
them.
A census will never exist that lists all resources available during a disaster. Disaster
management practitioners do not know what groups exist or who will ultimately be able
to provide services once a disaster occurs. They may not have a full understanding of the
critical dependencies for decision making (for example, who depends on whom and for
what). Such gaps in knowledge limit the ability to improvise effectively. Unpredictable
failure and re-emergence of networks add to the chaos. SNA research and the
development of tools that help practitioners sort through this kind of chaos could be
valuable.
Networks that emerge or re-emerge following a disaster may be unstable or loosely
constructed. Understanding how these emerging networks are organized is more complex
the bigger the disaster. Understanding how mistakes may occur during the re-emergence
of networks, and of how to correct them, is essential if practitioners are to use the
networks effectively in disaster response.
Networks of Networks
The way SNA tools can be used to understand how networks function has already
been discussed in this summary. SNA tools can be used beyond postdisaster case studies
2
The full text of the Freedom of Information Act (5 U.S.C. § 552, as amended by Public Law No. 104-231,
110 Stat. 3048) can be found at www.usdoj.gov/oip/foia_updates/Vol_XVII_4/page2.htm (accessed April
20, 2009).
4
________________________________________________________________________
Some practitioners at the workshop were concerned that homeland security policies
and funding structures often compel community leaders and emergency practitioners to
function reactively rather than proactively. Planning is often done within the constraints
of top-down policies that focus on protection and response rather than mitigation, and
few incentives exist for communities to work toward resiliency. Disaster preparedness
43
and continuity planning, although desirable, are often not well developed. Resiliency, a
concept not well understood among emergency management practitioners, is not a part of
the top-down emergency management culture. Policies are in place that can inhibit the
use of innovative tools that may foster community resilience.
At present, disincentives to prepare for disaster may exist because a community may
receive greater monetary benefits in the form of federal postdisaster aid. Although re-
search findings indicate that communities can expect a four-to-one return for every dollar
spent on disaster mitigation (Multihazard Mitigation Council, 2005), communities often
do not take advantage of the expected savings. The return is not realized unless a disaster
occurs and a reduction in recovery costs is observed. Additionally, mitigation planning
may be thwarted by an inability to decide where mitigation is needed. A community may
mitigate in the wrong way or be prepared for the wrong disaster. Under these circum-
stances, a community may suffer during a disaster and see no return on its investment.
Workshop participants have observed that at least some federal money is distributed
as incentive for mitigation. For example, the Federal Emergency Management Agency
(FEMA) instituted a pilot program to increase the federal costshare for communities who
developed FEMA-approved debris management plans.1 The program ended in 2008, but
it reflected congressional interest in reducing the cost of disasters and rewarding commu-
nities for better disaster preparedness. Many participants expressed the view that
incentive programs are helpful, but also expressed concern that they be carefully de-
signed to avoid draining on resources.
Some participants noted that incentives can also come from the private sector, for ex-
ample, through lower cost of insurance premiums for better construction or retrofitting
practices. Property owners, contractors, and suppliers could see immediate financial
benefits, and properties are better protected against disaster.
A wide range of computer-based and other social networks thrive at many community
levels. Determining how best to apply SNA to understand preparedness among these
networks and improve preparedness at the household, community, and organizational
levels is important. Understanding how to adapt preparedness plans and interventions to
serve at-risk populations, such as those disenfranchised from community networks, is
also important. Workshop participants noted that SNA could be used to understand how
communities organize around hazards and how people and organizations use networks
during disasters. The use of SNA for understanding the effective role of advocacy groups
(for example, those supporting special-needs individuals) in building resilience and
providing recovery assistance was also stressed. How social support and social
embeddedness influence community resilience, and the importance of public connectivity
in facilitating resilience are also topics meriting consideration.
SNA can be used to identify and study the characteristics and functions of trusted
leaders, organizations, and information sources within networks. By understanding how
leaders and organizations emerge within the computer-network environment under
1
See http://www.fema.gov/news/newsrelease.fema?id=46906 (accessed May 4, 2009).
different circumstances, and understanding the characteristics that allow them to become
trusted, emergency management practitioners could more effectively engage leaders and
organizations in improving community resilience. Understanding the constraints under
which decisions are made within organizations will also allow practitioners to target their
communication with the organizations effectively. SNA could be applied to government
organizations and networks, such as emergency response organizations, to study the at-
tributes and functions that make them successful during all phases of a disaster. Once
positive attributes are identified and understood, practitioners can build similar attributes
into their own organizations and networks.
The social network community is a complex and interdisciplinary enterprise requiring
the sharing of information in different ways among different members. Organization
charts cannot explain the important relationships and transactions that take place between
individuals and within and between organizations. SNA experts stated that better tools
exist to display the same information and that practitioners could benefit from learning
their use.
In general, those in authority benefit from the situational awareness of who is
working with whom, on what tasks, and under what circumstances. SNA tools could help
them visualize the important connections within networks. Effective disaster preparation
is dependent on knowing before a disaster what groups and organizations work well with
one another, which individuals know one another, and what sources of information are
trusted. This is especially relevant if communication systems fail during an event.
Workshop participants pointed out that optimal response depends on understanding what
links remain active and which will quickly be restored following infrastructure failure.
Critical links need to be identified and plans put in place so communication is sustainable
during total infrastructure failure.
Communication is essential to situational awareness. Situational awareness gives
practitioners an understanding of what is happening within the community to determine
who needs what resources, and who needs to know what information. Workshop partici-
pants repeatedly discussed the need for practitioners to understand how to use their
situational awareness to better disseminate the right information to the right people. SNA
tools could be used to identify the right people and the most efficient means of
communicating with them. SNA can then be applied to determine the impact of the
information once sent. For example, in 2008, people on the Texas coast failed to evacuate
despite warnings of the immanent arrival of Hurricane Ike. The perception among the
public was that a category 2 hurricane was not dangerous. However, some workshop
participants noted that had information of the storm’s hazards been broken down into the
dangers associated with wind, water, and storm surge, and had the information been
conveyed effectively, people in the community may have reacted differently and the
outcomes may have been less severe. SNA applied in this type of scenario could lead to
better outcomes.
Study of how SNA or similar analyses are applied in areas such as network-centric
warfare,2 counter terrorism, and public health could be applied to SNA for improving
community disaster resilience. The vocabulary of network-centric warfare is different
2
Network-centric warfare is a Department of Defense doctrine based on using information technology to
the military’s advantage (Alberts et al., 1999). A well-networked military improves situational awareness
and information sharing, resulting in the increased effectiveness of military missions.
from that used by social scientists during this workshop, but the goals are similar: to
understand and improve how information is sought and exchanged, and to develop an
action instrument that enables decision making. Understanding different patterns of
network analysis and the different reasons and conditions under which the analyses are
conducted could benefit both researchers and practitioners by helping them to
characterize and use social networks for the advantage of communities. According to
workshop participants, practitioners who are able to collect, analyze, understand, model,
and incorporate network data into their decision-making processes will likely be better
poised to help their communities become more resilient.
3
See http://www.pnpco.com/pn06001.html (accessed May 8, 2009).
4
See http://www.iaem.com/ (accessed May 8, 2009).
5
See http://www.nemaweb.org/home.aspx (accessed May 8, 2009).
Workshop participants stated that with the application of SNA, practitioners could
gain a better understanding of the thresholds at which communities fail, and could look at
different thresholds of community fragility in response to different levels of stress.
Empirical data on past disasters could allow estimates of failure thresholds for cities of
different size and complexity, and with different types of networks among emergency
response organizations. These kinds of post-event assessments of the effectiveness of
social networks and the prevention of their failures are important components of baseline
data. The data could allow the opportunity for researchers to document good practices
and understand the characteristics of a community that enable resilience or rapid
recovery. Participants also stated that comparative studies of networks that have emerged
following a variety of disasters would be helpful.
Researchers do not have the capacity to collect much of the data needed to support
SNA for building resilience, especially inter- and intraorganizational data. Many
workshop participants stated that there is a great unevenness in the data available to
populate databases, models, and SNA tools. As a result, comparative longitudinal studies
of community resilience and change have not been conducted to any great extent.
Because few resources are available to conduct much more than post-disaster case study
research, the collective knowledge of the research community is focused on local
systemic and episodic changes. The development of mechanisms for collecting network
data, similar to surveillance mechanisms used for epidemiological monitoring, could be
helpful. Additionally, workshop participants stated that data collection is underfunded,
and that funding mechanisms do not exist solely for collecting and managing the large
datasets required for SNA.
Baseline data as input to SNA can contribute to the understanding of how parts of a
network draw on available resources during normal operations, and how those resources
are stressed during a disaster. For example, baseline data on the normal operations of
supply carriers and their distribution routes could allow the application of SNA to
determine the best distribution options when service routes are disrupted or carriers be-
come unavailable. Under stress, systems can fail catastrophically. SNA can help explain
the extent of critical dependencies (who depends on whom) and the linkages between
them. Analysis may allow planning of interventions to avoid systemic or cascading
failures.
Workshop participants repeatedly stressed that the accuracy of network analysis,
monitoring, and intervention design cannot be certain without baseline data.
Workshop participants stated that the ability to communicate as a vital capacity for
resilience. Few things are more fundamental to community resilience than the ability to
access, communicate, and use information. Information may be in the form of baseline
data, media reports, and data that move across social networks. Development and transfer
to emergency management practitioners of the correct technologies linking SNA to tools
for collecting data, monitoring change, and conducting geospatial analyses are essential
for reliable communication. With such tools, practitioners could potentially measure the
quality of information received, determine what information is actionable, and determine
what constitutes the best actions in timeframes that are useful during a disaster. Such
tools could increase resilience by enabling two-way communication between emergency
managers and the public.
By understanding how information is spread, and by understanding how trust is built
between practitioners and the public and private sectors, practitioners may efficiently use
networks to spread helpful messages and control rumors. Identifying the behavioral
characteristics of those networks most effective at organizing themselves around hazards
could help community leaders foster those characteristics in the networks within their
own communities.
NEXT STEPS
Research Themes
of the disaster, available resources, and the level of authority at which decisions are
made. The application of SNA could improve the situational awareness of emergency
management practitioners by allowing them to understand and measure the status of
networks within their communities. Using knowledge gained through SNA, the necessary
interventions and conditions and network associations required for their success can be
identified. The best means of communicating and implementing interventions may be
developed.
Baseline Data
Baseline data include all manner of data regarding networks and their members.
Without baseline data, researchers and practitioners do not know how communities and
networks normally function; the impact of interventions may not be quantified; and the
effectiveness of communication and operations may not be measured. Without a measure
of community capacities to adapt to stress, interventions may not be effectively targeted
for maximum benefit. Little is known, for example, about who populates the formal,
governmental networks responsible for a region’s disaster management or how they
integrate with other social networks that reside in civil society. Without this baseline
level of knowledge, it is difficult to evaluate how the compositions of social networks
evolve and how this relates to resilience levels. Though workshop participants empha-
sized the importance of baseline data, current research funding makes the collection and
management of baseline data not feasible.
Validation Techniques
New networking technologies allow large amounts of data to travel quickly through
networks. Workshop participants observed that mechanisms to validate new data, net-
work models, and decisions made using SNA and related tools would be valuable to
practitioners and scientists. Practitioners described needing mechanisms that vet for
accuracy of data traveling through networks, and indicate whether information requires
action or response. Practitioners need a means to categorize data as good, bad, redundant,
and actionable.
New and more refined data-gathering techniques could result in better social network
models. For example, workshop participants frequently stressed the importance of devel-
oping the means to obtain proprietary and personal data for SNA, while preserving the
privacy of individuals and institutions. Data, such as who communicates with whom
within and between private sector organizations and what kinds of people receive certain
medical treatment under certain circumstances, provide important insights into the nature
of networks and their members.
Exploring other broader social issues where SNA has been or could be applied may
provide useful information related to the application of SNA for building community
resilience. Building resilience is not only about preparation for disasters. Research on
how communities deal with issues such as ethnic oppression may yield a rich and
pertinent literature regarding community resilience.
Although addressing these barriers was not directly part of the charge given the
workshop planning committee, many participants stated that the barriers could affect the
effectiveness of a future research agenda and slow the adoption of SNA tools by
practitioners. Strategies to overcome these barriers were suggested by workshop
participants and are summarized in the next paragraphs.
Workshop participants discussed how current strategies for funding research and its
translation into practice are not adequate to address the large-scale and complex social
science issues raised. New funding paradigms to accommodate larger and longer-term
studies would benefit both the research and practice communities. One result could be
better baseline data from which progress can be measured. Incentives to encourage
multidisciplinary research and the rapid response efforts needed immediately following
disasters could lead to results that are more immediately useful to practitioners.
Workshop participants expressed the view that research collaborations among researchers
and practitioners, and between public and private entities, could enhance the adoption of
SNA techniques among practitioners. Issues associated with barriers of access to
infrastructure and data could also be overcome. Collaboration between researchers and
practitioners, with input from the private sector, could result in the most relevant
research, tools, and data for decision making.
Among the workshop participants, some practitioners and researchers expressed con-
cern that current homeland security priorities tend to encourage a focus on antiterrorism
activities within the emergency management community. Some suggested that sources of
community stress need to be adequately assessed to confirm whether a focus on
antiterrorism is locally warranted. A better understanding of community stressors could
allow for more informed allocation of resources.
information, and physical resources. Encouraging the creation of robust and flexible
networks during times of normal operation could enable networks to be resilient during
times of stress.
Many of the same capacities that allow a community to function during times of dis-
aster (e.g., being well informed, well networked, and possessing the ability to respond to
situations with creativity and flexibility) are those that allow a community to thrive dur-
ing normal times. Many workshop participants expressed the view that by increasing the
capacity for effective communication through social networks, a community may be cre-
ated that is resilient to a broad range of stressors. Investing in building of community
resilience is highly likely to yield rapid returns through the creation of stronger and
healthier communities.
References
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Appendix A
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Committee Biographies
57
science. In her work, she examines how cognitive, social, and institutional factors affect
individual, team, social, and policy outcomes. She is the author or coauthor of numerous
books and articles in the areas of computational social and organizational science and
dynamic network analysis. She served on the organizing committee for the National
Research Council Workshop on Statistical Analysis of Networks and the Panel on
Modeling Human Behavior and Command Decision Making: Representations for
Military Simulations. She is a member of the Academy of Management, International
Network for Social Network Analysis, American Sociological Society, American
Association for the Advancement of Science, Informs, and Sigma Xi. In 2001, she re-
ceived the lifetime achievement award from the sociology and computers section of the
American Sociological Association. She is a founding and current editor of
Computational and Mathematical Organization Theory. She received her Ph.D. in
sociology from Harvard University.
APPENDIX A 59
Clinic and the Emergency Information Infrastructure Partnership and is on the advisory
council for the Center for Regional Disaster Resilience. He is a past president of the
Washington State Emergency Management Association. Mr. Holdeman received a B.A. in
education from Concordia University.
Monica Schoch-Spana is a senior associate with the Center for Biosecurity at the
University of Pittsburgh Medical Center (UPMC) and an assistant professor in the School
of Medicine Division of Infectious Diseases. The Center for Biosecurity works to affect
policy and practice in ways that lessen the illness, death, and civil disruption that would
follow large epidemics, whether they occur naturally or result from the use of a biological
weapon. Dr. Schoch-Spana, a medical anthropologist, has led research, education, and
advocacy efforts to encourage greater consideration by authorities of the general public’s
capacity to confront bioattacks and epidemics constructively. She recently chaired the
Center’s Working Group on Citizen Engagement in Health Emergency Planning, and was
the principal organizer for the 2006 U.S.-Canada summit on Disease, Disaster, and
Democracy: The Public’s Stake in Health Emergency Planning. In 2003, she organized
the national summit, Leadership During Bioterrorism: The Public as an Asset, Not a
Problem, and chaired the Working Group on “Governance Dilemmas” in Bioterrorism
Response that issued consensus recommendations to mayors, governors, and top health
officials nationwide in 2004. Dr. Schoch-Spana has served on the NRC Steering
Committee of the Disasters Roundtable, the Committee on Educational Paradigms for
Homeland Security, and the Committee on Standards and Policies for Decontaminating
Public Facilities Affected by Exposure to Harmful Biological Agents: How Clean is
Safe? She serves on the faculty for the National Consortium for the Study of Terrorism
and Responses to Terrorism, a university center of excellence supported by the U.S.
Department of Homeland Security. Dr. Schoch-Spana helped establish the Biosecurity
Center of UPMC in 2003; prior to that she worked at the Johns Hopkins Center for
Civilian Biodefense Strategies, starting in 1998. She received a Ph.D. in cultural
anthropology from Johns Hopkins University and a B.A. from Bryn Mawr College.
Appendix B
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Schoon, I. 2006. Risk and Resilience: Adaptations in Changing Times. Cambridge, U.K.:
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61
Scott, J. 2000. Social Network Analysis: A Handbook. Newberry Park, Calif.: SAGE
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Wasserman, S., and K. Faust. 1994. Social Network Analysis: Methods and Applications.
Cambridge, U.K.: Cambridge University Press, 825 pp.
Articles
APPENDIX B 63
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Articles
APPENDIX B 65
Appendix C
________________________________________________________________________
Workshop Participants
67
Sammantha Magsino
Board on Earth Sciences and Resources
The National Academies
Matthew Morrison
Pacific NorthWest Economic Region
Fran H. Norris
National Center for Disaster Mental Health
Research
Dartmouth Medical School
Jennifer B. Nuzzo
Center for Biosecurity
University of Pittsburgh Medical Center
Appendix D
________________________________________________________________________
The workshop agenda included breakout sessions during which workshop participants
were divided into two groups. Participants of each concurrent session were to discuss
specific issues related to themes defined by the workshop planning committee. The
planning committee described the themes and provided questions to guide discussions.
This section includes the text of materials regarding the concurrent breakout sessions
provided to the participants prior to the workshop.
CONCURRENT SESSIONS
This session examines opportunities for social network analysis in understanding and
facilitating preparedness and response to emergencies in two different venues: networks
among and between organizations and networks within local communities. In
organizational response (Session 3a), we are interested in how more productive
interactions and flexibility for improvisation and how these can be enhanced through
social network analysis and social networking technology. For local networks within
communities and among individuals (Session 3b), the concern is how to empower and
engage such communities and foster collective behavior in preparing for, responding to,
and recovering from disasters.
This session examines opportunities for social network analysis in understanding and
facilitating preparedness and response to emergencies in two different venues: networks
among and between organizations and networks within local communities. In
organizational response (Session 3a), we are interested in how more productive
interactions and flexibility for improvisation and how these can be enhanced through
social network analysis and social networking technology. Participants are provided the
following questions to help guide the discussion. The session rapporteur will summarize
69
1. How do social networks operate organization to organization and what are current
knowledge gaps in our understanding of their functioning?
2. To what extent is this currently measured using Social Network Analysis (SNA)?
3. To what extent is SNA used and how can SNA facilitate, maximize, and foster pre-
conditions that will permit improvisational response during disasters?
4. What SNA research or change in practice is required to facilitate more productive
interaction between the Incident Command System (ICS) and the emergent
networks and responders? What tools would be most useful in this effort?
5. How can social networking technology be used to maximize the utility of emergent
responders?
6. How can SNA be used in choosing what social networking technologies should be
utilized?
7. What are the gaps in knowledge and technology that inhibit the application of social
network tools and theory to improvisational response?
8. What are the barriers in terms of training, technology, and policy to applying social
network theory and tools to improvisational response?
This session examines opportunities for social network analysis in understanding and
facilitating preparedness and response to emergencies in two different venues: networks
among and between organizations and networks within local communities. For local
networks within communities and among individuals (Session 3b), the concern is how to
empower and engage such communities and foster collective behavior in preparing for,
responding to, and recovering from disasters. Participants are provided the following
questions to help guide the discussion. The session rapporteur will summarize the
discussion for all workshop participants during the plenary session following the
discussion.
1. What Social Network Analysis (SNA) tools are used currently to identify pre-
existing networks in communities?
2. How is and can SNA be used to understand the collective and emergent behavior of
social networks before, during, and after the disaster cycle
3. How can the collective and emergent behavior of social networks be fostered and
directed before, during, and after the disaster cycle?
4. What technologies are most appropriate for engaging and empowering social
networks at the community level?
5. What SNA tools can be used to determine what we don’t know about how such
social networks are built, function, grow, prosper during both pre- and post-
disaster? What are the gaps in knowledge and technology that inhibit the
application of social network tools and theory to improvisational response?
6. What are the barriers in terms of training, technology, and policy to applying social
network theory and tools to improvisational response?