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Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
Community Structure in Congressional Conversation Networks
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Community Structure in Congressional Conversation Networks

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Slides from ICA 2012

Slides from ICA 2012

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  • 1. COMMUNITY STRUCTURE INCONGRESSIONALCONVERSATION NETWORKSOr, the paper formerly known asRelationships Among Twitter ConversationNetworks, Language Use, and CongressionalVotingLibby Hemphill, Jahna Otterbacher, andMatthew Shapiro
  • 2. What do we expect to see?• Interaction with constituents 5,8,10• Polarization, divided communities 1,3,4,8• More activity among Republicans 9• More activity among Senators 9• Similar presentations among men and women 7
  • 3. Legend for graphsEdge PropertiesColor Gray = same party Yellow = different partiesNode PropertiesColor Red = Republican Blue = Democrat Yellow = IndependentShape Solid square = House Solid circle = SenateSize In degreeOpacity Out degree
  • 4. April 12, 2012 Shapiro, Hemphill, and OtterbacherCongress mentioning each other:Excluding self-loops
  • 5. April 12, 2012 Shapiro, Hemphill, and OtterbacherCongress mentioning each other:including self-loops
  • 6. April 12, 2012 Shapiro, Hemphill, and OtterbacherHouse only
  • 7. April 12, 2012 Shapiro, Hemphill, and OtterbacherSenate only
  • 8. Predicting Connections (1) (2) (3) (4) crossparty crosschamber crossparty crosschamberRepublican -0.308*** 0.107** -0.325*** 0.0908** (-12.86) (3.27) (-13.15) (2.71)Senate 0.172*** 2.715*** 0.180*** 2.724*** (5.46) (74.83) (5.69) (74.48)Male 0.0925** 0.0944* (2.79) (2.12)_cons -0.230*** -1.943*** -0.299*** -2.014*** (-12.21) (-71.46) (-9.62) (-46.26)N = 29,597t statistics in parentheses* p < 0.05, ** p < 0.01, *** p < 0.001
  • 9. Results• Low density indicates low cohesion 6• Republicans, Senators, and males more likely to mention across chambers• Senators and men more likely to mention across party lines• Conservatives mention each other more 1• Explicitly engage small subset of those under surveillance 2
  • 10. Takeaways• New medium, not new behavior 11• Congress less polarized than political blogosphere 1• Echo chamber more than broadcast medium
  • 11. Contact us• Libby Hemphill (libby.hemphill@iit.edu)• Jahna Otterbacher (jotterba@iit.edu)• Matt Shapiro (mshapir2@iit.edu)• Illinois Institute of Technology• info@casmlab.org• http://www.casmlab.org/projects/publicofficials/
  • 12. References1. Adamic, L. A., & Glance, N. (2005). The political blogosphere and the 2004 U.S. election: Divided they blog. Proceedings of the 3rd International Workshop on Link Discovery (LinkKDD ’05) (pp. 36–43). New York, NY, USA: ACM. Retrieved from http://portal.acm.org/citation.cfm?id=11342772. Bakshy, E., Hofman, J. M., Watts, D. J., & Mason, W. A. (2011). Everyone’s an influencer: Quantifying influence on Twitter. Proceedings of the fourth ACM International Conference on Web Search and Data Mining (WSDM ’11) (pp. 65-74). New York: ACM.3. Conover, M. D., Ratkiewicz, J., Francisco, M., Goncalves, B., Flammini, A., & Menczer, F. (2011). Political polarization on Twitter. Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media (pp. 89-96). Palo Alto: AAAI Press.4. Iyengar, S., & Hahn, K. S. (2009). Red Media, Blue Media: Evidence of Ideological Selectivity in Media Use. Journal of Communication, 59(1), 19-39. Retrieved from http://doi.wiley.com/10.1111/j.1460-2466.2008.01402.x5. Johnson, D. W. (2004). Congress Online: Bridging the Gap Between Citizens and Their Representatives (Google eBook) (p. 242). Psychology Press. Retrieved from http://books.google.com/books?hl=en&lr=&id=0vgVHQTpygkC&pgis=16. Livne, A., Simmons, M. P., Adar, E., & Adamic, L. A. (2011). The party is over here: Structure and content in the 2010 election. 5th International AAAI Conference on Weblogs and Social Media (ICWSM). Palto Alto: AAAI Press.7. Niven, D., & Zilber, J. (2001). Do Women and Men in Congress Cultivate Different Images? Evidence from Congressional Web Sites. Political Communication, 18(4), 395-405. Routledge. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/105846001526471008. Parmelee, J. H., & Bichard, S. L. (2011). Politics and the Twitter Revolution: How Tweets Influence the Relationship Between Political Leaders and the Public (Google eBook) (Vol. 2011, p. 247). Lexington Books. Retrieved from http://books.google.com/books?id=KPn5Pnkhx7sC&pgis=19. Wang, (Bryan) M., Hanna, A., Sayre, B., Yang, J., Mirer, M., Kim, M., & Shah, D. (2011). Who is following me? An analysis of candidate egocentric networks on Twitter in the 2010 midterm elections. 2011 Midwest Political Science Association Annual National Conference. Chicago: MPSA.10. Williams, C. B., & Gulati, G. J. (2010). Communicating with constituents in 140 characters or less: Twitter and the diffusion of technology innovation in the United States Congress . SSRN eLibrary. Chicago: SSRN. Retrieved from http://ssrn.com/paper=181705311. Xenos, M. A., & Foot, K. A. (2005). Politics as usual, or politics unusual? Position taking and dialogue on campaign websites in the 2002 U.S. Elections. Journal of Communication, 55(1), 169-185. Retrieved from http://doi.wiley.com/10.1111/j.1460-2466.2005.tb02665.x

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