Reflecting Community Events and Social Interactions through Archived Social Media
Pages 223 - 231
Abstract
Webpages and social media associated with geographic communities reflect local events and social interactions. When we archive and analyze these aggregated data of events and interactions over time, we observe a kind of history of a given period for a geographic area, similar to a collection of local information, newspaper stories and citizen commentary. In our data set, we have syndicated (RSS) feeds of information and news posted on websites and social media of local organizations, including government, as well as tweets, blogs and Facebook posts made by organizations and individuals. This kind of collection has built-in biases, of course, just as local print media and online newsgroups do. Nonetheless, the aggregated content reflects a geographic community of users, comprised of individuals as well as organizations, such as, government agencies, businesses, local voluntary associations and residents. We analyzed our data using the standard Latent Dirichlet Allocation (LDA) algorithm and the open source tool NodeXL to identify topics and their changes over time. We also created social graphs based on retweets and @ mentions and quantified exchanges around main topics. Our findings show: 1) distinct topics 2) large and small social interactions around a variety of topics, and 3) patterns suggesting what are called 'community clusters' and 'tight crowd' types of conversations.
References
[1]
S. Ahuja, M. Pérez-Quiñones and A. Kavanaugh Rethinking Local Conversations on the Web. Center for the Study of Language and Information, Comuter Science Lecture Series, Springer, New York, 2009.
[2]
P. Bhattacharya, S. Ghosh, J. Kulshrestha, M. Modal, M.B. Zafar, N. Ganguly and K.P. Gummadi. Deep Twitter Diving: Exploring Topical Groups in Microblogs at Scale. In Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW '14) (Baltimore, MD, 2014). ACM, New York, 2014.
[3]
D. Blei and J. Lafferty. Topic models. In A. Srivastava and M. Sahami (Eds.) Text Mining: Classificaton, Clustering and Appications, Chapman & Hall, London, 2009.
[4]
d. boyd, S. Golder and G. Lotan Tweet, Tweet, Retweet: Conversational aspects of retweeting on Twitter. In IEEE Proceedings of HICSS-43, 2010.
[5]
A. Cohill and A. Kavanaugh Community Networks: Lessons from Blacksburg, Virginia, Artech House, Norwood, 1997.
[6]
J. Cranshaw, R. Schwartz, J.I. Hong and N. Sadeh. The Livehoods Project: Utilizing social media to understand the dynamics of a city. In Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media (CWSM-12) (Dublin, Ireland) AAAI, 2012.
[7]
M. de Choudhury, N. Diakopoulos and M. Naaman. Unfolding the event landscape on Twitter: Classification and exploration of user categories. In Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW '12) (Seattle, WA, 2012). ACM, New York, 2012.
[8]
M. Gurstein Community Informatics: Enabling Communities with Information and Communications Technologies. Idea Group, Hershey, PA, 2000.
[9]
B. Hanrahan, S. Ahuja, M. Perez-Quinones and A. Kavanaugh Evaluating Software for Communities Using Social Affordances. In Proceedings of the 2011 ACM CHI Conference on Human Factors in Computing Systems, ACM, New York, 2011.
[10]
D. Hansen, D. Rotman, E. Bonsignore, N. MilicFrayling, E.M. Rodriges, M. Smith, B. Shneiderman and T. Capone. Do You Know the Way to SNA? A process model for analyzing and visualizing social media data. Technical Report HCIL-2009-17, University of Maryland, College Park, MD, 2009.
[11]
D. Hansen, B. Shneiderman and M. Smith Analyzing Social Media Networks with NodeXL: Insights from a connected world. Morgan Kaufmann, Burlington, MA, 2010.
[12]
A. Java, T. Finin, X. Song and B. Tseng. Why We Twitter: Understanding microblogging usage and communities. In Proceedings of the Joint 9th WEBKDD and 1st SNA-KDD Workshop '07 (San Jose, California, August 12, 2007). ACM, New York, 2007.
[13]
A. Kavanaugh, D. Reese, J.M. Carroll and M.B. Rosson Weak Ties in Networked Communities Kluwer Academic Publishers, The Netherlands, 2003.
[14]
A. Kavanaugh, J.M. Carroll, M.B. Rosson, T.T. Zin and D.D. Reese Community networks: Where offline communities meet online Journal of Computer-Mediated Communication, 10, 4, (2005).
[15]
A. Kavanaugh, M. Pérez-Quiñones, J.C. Tedesco and W. Sanders Toward a Virtual Town Square in the Era of Web 2.0, 279--294. In J. Hunsinger, L. Klastrup and M. Allen (Eds.) International Handbook of Internet Research, Springer, New York, 2010.
[16]
A. Kavanaugh, A. Ahuja, S. Gad, S. Neidig, M.A. Pérez-Quiñones, N. Ramakrishnan and J. Tedesco (Hyper) local news aggregation: Designing for social affordances. Government Information Quarterly, 31, 1 (2014), 30--41.
[17]
A. Kavanaugh, A. Ahuja, M. Perez-Quinones, J. Tedesco, K. Madondo and S. Krishnan Encouraging Civic Participation through News Aggregation. Information Polity, 19, 1--2 (2014), 35--56.
[18]
J. Kim, R. Wyatt and E. Katz News, talk, opinion, participation: the part played by conversation in deliberative democracy. Political Communication, 16, 4 (1999), 361--385.
[19]
P. Purcell The Networked Neighborhood: The Online Community in Context. Springer, New York, 2006.
[20]
B. Roble, J. Cheng and M. Sbitani. Tweets Region X. CS 4624: Hypertext and Multimedia Capstone Course Report, Computer Science, Virginia Tech, 2014.
[21]
D. Schuler New Community Networks: Wired for Change. Addison-Wesley, Reading, MA, 1996.
[22]
M.A. Smith, L. Rainie and B. Shneiderman Mapping Twitter Topic Networks: From polarized crowds to community clusters. Pew Research Internet Project, Washington DC, 2014.
[23]
C. Tauro, S. Ahuja, M. Pérez-Quiñones, A. Kavanaugh and P. Isenhour. Deliberation in the Wild: A Visualization Tool for Blog Discovery and Citizen-to-Citizen Participation. In Proceedings of the 9th Annual International Conference on Digital Government Research (dg.o 2008) (Montreal, Canada, May, 18--21, 2008). ACM, New York, 2008.
[24]
US Census Bureau: Quick Facts. US Department of Commerce, Washington DC.
Recommendations
The diffusion of misinformation on social media
This study examines dynamic communication processes of political misinformation on social media focusing on three components: the temporal pattern, content mutation, and sources of misinformation. We traced the lifecycle of 17 popular political rumors ...
Social Media: An Exploratory Study of Information, Misinformation, Disinformation, and Malinformation
AbstractThe widespread use of social media all around the globe has affected the way of life in all aspects, not only for individuals but for businesses as well. Businesses share their upcoming events, reveal their products, and advertise to their ...
Believability and Harmfulness Shape the Virality of Misleading Social Media Posts
WWW '23: Proceedings of the ACM Web Conference 2023Misinformation on social media presents a major threat to modern societies. While previous research has analyzed the virality across true and false social media posts, not every misleading post is necessarily equally viral. Rather, misinformation has ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © 2017 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
In-Cooperation
- IOS Press: IOS Press
- Digital Government Society of North America
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 07 June 2017
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
dg.o '17
dg.o '17: 18th Annual International Conference on Digital Government Research
June 7 - 9, 2017
NY, Staten Island, USA
Acceptance Rates
dg.o '17 Paper Acceptance Rate 66 of 114 submissions, 58%;
Overall Acceptance Rate 150 of 271 submissions, 55%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 122Total Downloads
- Downloads (Last 12 months)8
- Downloads (Last 6 weeks)1
Reflects downloads up to 20 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in