research-article

Towards the automated social analysis of situated speech data

Authors:

Tanzeem Choudhury,

James A. KittsAuthors Info & Claims

UbiComp '08: Proceedings of the 10th international conference on Ubiquitous computing

Pages 168 - 171

https://doi.org/10.1145/1409635.1409658

Published: 21 September 2008 Publication History

Abstract

We present an automated approach for studying fine-grained details of social interaction and relationships. Specifically, we analyze the conversational characteristics of a group of 24 individuals over a six-month period, explore the relationship between conversational dynamics and network position, and identify behavioral correlates of tie strengths within a network. The ability to study conversational dynamics and social networks over long time scales, and to investigate their interplay with rigor, objectivity, and transparency will complement the traditional methods for scientific inquiry into social dynamics. They may also enable socially aware ubiquitous computing systems that are cognizant of and responsive to the user's engagement with her social environment.

References

[1]

N. Baym, Y. B. Zhang, and M. C. Lin. Social interactions across media: Interpersonal communication on the internet, telephone and face-to-face. New Media and Society, 6:299--318, June 2004.

[2]

T. Choudhury, G. Borriello, S. Consolvo, D. Haehnel, B. Harrison, B. Hemingway, J. Hightower, P. Klasnja, K. Koscher, A. LaMarca, J. Landay, L. LeGrand, J. Lester, A. Rahimi, A. Rea, and D. Wyatt. The mobile sensing platform: An embedded system for activity recognition. IEEE Pervasive Computing, 7(2):32--41, April--June 2008.

Digital Library

[3]

R. Donovan. Trainable Speech Synthesis. PhD thesis, Cambridge University, 1996.

[4]

S. L. Feld. The focused organization of social ties. Am J Sociol, 86(5):1015--1035, March 1981.

[5]

J. Fogarty, S. E. Hudson, C. G. Atkeson, D. Avrahami, J. Forlizzi, S. Kiesler, J. C. Lee, and J. Yang. Predicting human interruptibility with sensors. ACM Trans. Comput.-Hum. Interact., 12(1):119--146, 2005.

Digital Library

[6]

D. R. Gibson. Taking turns and talking ties: Networks and conversational interaction. Am J Sociol, 110(6):1561--97, May 2005.

[7]

S. M. Goodreau, J. A. Kitts, and M. Morris. Birds of a feather, or friend of a friend? Using exponential random graph models to investigate adolescent social networks. Demography, 45(4), November 2008.

[8]

J. A. Kitts, H. I. Thielmann, E. Gleave, and R. Wang. Survey of Social Relations and Interests Among Graduate Students. Center for Statistics and the Social Sciences, Seattle, WA, 2006.

[9]

G. Kossinets and D. J. Watts. Empirical analysis of an evolving social network. Science, 311:88--90, 2006.

[10]

T. Quatieri. Discrete-time Speech and Signal Processing: Principles and Practice. Prentice Hall, 2001.

Digital Library

[11]

B. Schilit, N. Adams, and R. Want. Context-aware computing applications. In Proc. of Workshop on Mobile Computing Systems and Applications, 1994.

Digital Library

[12]

S. Wasserman and K. Faust. Social Network Analysis: Methods and Applications. Cambridge University Press, 1994.

[13]

D. Wyatt, T. Choudhury, and J. Bilmes. Conversation detection and speaker segmentation in privacy sensitive situated speech data. In Proceedings of Interspeech, 2007.

[14]

D. Wyatt, T. Choudhury, and J. Bilmes. Learning hidden curved exponential random graph models to infer face-to-face interaction networks from situated speech data. In Proc. of AAAI, 2008.

Digital Library

[15]

D. Wyatt, T. Choudhury, and H. Kautz. Capturing spontaneous conversation and social dynamics: A privacy sensitive data collection effort. In Proc. of ICASSP, 2007.

Cited By

Chng ESeyam MYao WSchneider B(2022)Toward capturing divergent collaboration in makerspaces using motion sensorsInformation and Learning Sciences10.1108/ILS-08-2020-0182123:5/6(276-297)Online publication date: 29-Mar-2022
https://doi.org/10.1108/ILS-08-2020-0182
Müller JFàbregues SGuenther ERomano M(2019)Using Sensors in Organizational Research—Clarifying Rationales and Validation Challenges for Mixed MethodsFrontiers in Psychology10.3389/fpsyg.2019.0118810Online publication date: 24-May-2019
https://doi.org/10.3389/fpsyg.2019.01188
Toyama KSumi Y(2018)Quick Browsing of Shared Experience Videos Based on Conversational Field DetectionMobile Computing, Applications, and Services10.1007/978-3-319-90740-6_3(40-55)Online publication date: 6-May-2018
https://doi.org/10.1007/978-3-319-90740-6_3
Show More Cited By

Recommendations

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science

New technologies have made it possible to collect information about social networks as they are acted and observed in the wild, instead of as they are reported in retrospective surveys. These technologies offer opportunities to address many new research ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

UbiComp '08: Proceedings of the 10th international conference on Ubiquitous computing

September 2008

404 pages

ISBN:9781605581361

DOI:10.1145/1409635

General Chairs:
Hee Yong Youn
Sungkyunkwan University, Korea
,
We-Duke Cho
Ajou University, Korea
,
Program Chairs:
Joe McCarthy,
James Scott,
Woontack Woo

Copyright © 2008 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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2008

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Division of Information and Intelligent Systems

Conference

UbiComp08

UbiComp08: The 10th International Conference on Ubiquitous Computing

September 21 - 24, 2008

Seoul, Korea

Acceptance Rates

Overall Acceptance Rate 764 of 2,912 submissions, 26%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

22
Total Citations
View Citations
393
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Chng ESeyam MYao WSchneider B(2022)Toward capturing divergent collaboration in makerspaces using motion sensorsInformation and Learning Sciences10.1108/ILS-08-2020-0182123:5/6(276-297)Online publication date: 29-Mar-2022
https://doi.org/10.1108/ILS-08-2020-0182
Müller JFàbregues SGuenther ERomano M(2019)Using Sensors in Organizational Research—Clarifying Rationales and Validation Challenges for Mixed MethodsFrontiers in Psychology10.3389/fpsyg.2019.0118810Online publication date: 24-May-2019
https://doi.org/10.3389/fpsyg.2019.01188
Toyama KSumi Y(2018)Quick Browsing of Shared Experience Videos Based on Conversational Field DetectionMobile Computing, Applications, and Services10.1007/978-3-319-90740-6_3(40-55)Online publication date: 6-May-2018
https://doi.org/10.1007/978-3-319-90740-6_3
Jang HChoe SGunkel SKang SSong J(2017)A System to Analyze Group Socializing Behaviors in Social PartiesIEEE Transactions on Human-Machine Systems10.1109/THMS.2016.263491847:6(801-813)Online publication date: Dec-2017
https://doi.org/10.1109/THMS.2016.2634918
Gu JGao BChen YJiang LGao ZMa XMa YWoo WJin J(2017)Wearable Social Sensing: Content-Based Processing Methodology and ImplementationIEEE Sensors Journal10.1109/JSEN.2017.275428917:21(7167-7176)Online publication date: 1-Nov-2017
https://doi.org/10.1109/JSEN.2017.2754289
Johannes BSitev AVinokhodova ASalnitski VSavchenko EArtyukhova ABubeev YMorukov BTafforin CBasner MDinges DRittweger J(2015)Wireless Monitoring of Changes in Crew Relations during Long-Duration Mission SimulationPLOS ONE10.1371/journal.pone.013481410:8(e0134814)Online publication date: 7-Aug-2015
https://doi.org/10.1371/journal.pone.0134814
Feese SBurscher MJonas KTröster G(2014)Sensing spatial and temporal coordination in teams using the smartphoneHuman-centric Computing and Information Sciences10.1186/s13673-014-0015-94:1Online publication date: 28-Sep-2014
https://doi.org/10.1186/s13673-014-0015-9
Gao BWoo W(2014)Wearable Audio Monitoring: Content-Based Processing Methodology and ImplementationIEEE Transactions on Human-Machine Systems10.1109/THMS.2014.230069844:2(222-233)Online publication date: Apr-2014
https://doi.org/10.1109/THMS.2014.2300698
Rahman MHossain MSaddik A(2014)Context-aware multimedia services modelingMultimedia Tools and Applications10.1007/s11042-013-1595-573:3(1147-1176)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1007/s11042-013-1595-5
Rahman MKim HSaddik AGueaieb W(2014)A context-aware multimedia framework toward personal social network servicesMultimedia Tools and Applications10.1007/s11042-012-1302-y71:3(1717-1747)Online publication date: 1-Aug-2014
https://dl.acm.org/doi/10.1007/s11042-012-1302-y
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents