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 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
 Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting
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Doing What I Say: Connecting Congressional Social Media Behavior and Congressional Voting

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Given at MPSA 2012 …

Given at MPSA 2012
Public officials’ communication has been explored at length in terms of how such their statements are conveyed in the traditional media, but minimal research has been done to examine their communication via social media. This paper explores the kinds of statements U.S. officials are making on Twitter in terms of the actions they are trying to achieve. We then analyze the correlation between these statements, Congressional communication network structures, and voting behavior. Our analysis leverages over 29,000 tweets by members of Congress in conjunction with existing DW-NOMINATE voting behavior data. We find that pro-social and self-promoting statements correlate with Congressional voting records but that position within the Congressional communication network does not correlate with voting behavior.

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  1. DOINGWHAT I SAYCONNECTING CONGRESSIONALSOCIAL MEDIA BEHAVIOR ANDCONGRESSIONAL VOTING
  2. PROJECT TEAM• Matt Shapiro• Libby Hemphill• Jahna Otterbacher• Drexler James• W. David WorkIllinois Institute of Technologyinfo@casmlab.orghttp://www.casmlab.org/projects/publicofficials/April 12, 2012Shapiro, Hemphill, and Otterbacher
  3. OVERVIEW• Twitter overview• Communication networks on Twitter• Coding for action• Using Twitter for predictionApril 12, 2012Shapiro, Hemphill, and Otterbacher
  4. TWITTEROVERVIEWApril 12, 2012Shapiro, Hemphill, and Otterbacher
  5. TWITTER HOMEApril 12, 2012Shapiro, Hemphill, and Otterbacher
  6. TWITTERCONVENTIONS• @username and .@username• #hashtag• RT and MTApril 12, 2012Shapiro, Hemphill, and Otterbacher
  7. WHYCONGRESSANDTWITTER?April 12, 2012Shapiro, Hemphill, and Otterbacher
  8. WHAT DIDWE SEE?April 12, 2012Shapiro, Hemphill, and Otterbacher
  9. 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 degreeApril 12, 2012Shapiro, Hemphill, and Otterbacher
  10. CONGRESS MENTIONING EACH OTHER:EXCLUDING SELF-LOOPSApril 12, 2012Shapiro, Hemphill, and Otterbacher
  11. CONGRESS MENTIONING EACH OTHER:INCLUDING SELF-LOOPSApril 12, 2012Shapiro, Hemphill, and Otterbacher
  12. HOUSE ONLYApril 12, 2012Shapiro, Hemphill, and Otterbacher
  13. SENATE ONLYApril 12, 2012Shapiro, Hemphill, and Otterbacher
  14. NETWORKPROPERTIES• Low transitivity• Low density• High distance• No evidence of higher-order structureApril 12, 2012Shapiro, Hemphill, and Otterbacher
  15. INTERPRETINGRESULTS• Low density indicates low cohesion (Livne et al. 2011)• Congress much like the public • Conservatives mention each other more (Adamic & Glance 2005) • Explicitly engage small subset of those under surveillance (Bakshy et al. 2011)• New medium, not new behavior • Avoiding issue dialogue (Huckfeldt et al. 1995) • No real role of third parties (Xenos & Foot 2005)April 12, 2012Shapiro, Hemphill, and Otterbacher
  16. CODING FOR ACTIONCode Definition N Cohen’s kappaNarrating Telling a story about their day, 173 0.83 describing activitiesPositioning Situating ones self in relation to 405 0.87 another politician or political issueDirecting to Pointing to a resource URL, telling 465 0.70information you where you can get more infoRequesting Explicitly telling followers to go do 15 0.70action something online or in personThanking Says nice things about or thanks 57 0.90 someone elseApril 12, 2012Shapiro, Hemphill, and Otterbacher
  17. MAKINGPREDICTIONSItem MeasureSize of audience FollowersSurveillance FriendsFrequency TweetsPolarizing DW-NOMINATEApril 12, 2012Shapiro, Hemphill, and Otterbacher
  18. MAKINGPREDICTIONSItem MeasureSize of audience FollowersSurveillance FriendsFrequency TweetsPolarization DW-NOMINATEApril 12, 2012Shapiro, Hemphill, and Otterbacher
  19. PREDICTINGAUDIENCEMeasure Coefficient Measure CoefficientNarrative -0.15 Male -0.75* (0.10) (0.11)Positioning 0.19* Republican 1.20* (0.09) (0.09)Providing info 0.23* Senate 1.02* (0.08) (0.09)Requesting action 0.23 (0.28)Thanking 0.08 (0.16)April 12, 2012Shapiro, Hemphill, and Otterbacher
  20. PREDICTINGPOLARIZING VOTESMeasure CoefficientNarrative -0.05 (0.05)Positioning 0.09* (0.04)Providing info 0.07* (0.04)Requesting action -0.13 (0.17)Thanking -0.24* (0.09)April 12, 2012Shapiro, Hemphill, and Otterbacher
  21. USING TWITTERBEHAVIOR FORPREDICTIONS• Positioning and providing info predict size of audience• Positioning predicts extreme voting• Thanking predicts centrist votingApril 12, 2012Shapiro, Hemphill, and Otterbacher
  22. WHATNEXT?April 12, 2012Shapiro, Hemphill, and Otterbacher
  23. FUTURE WORK• Who is not connecting and why?• What’s the nature of the cross-party mentioning?• Are there reciprocal patterns?• What relationships exist between conversation networks and offline networks?• What impact does gender have on social media communication behavior?April 12, 2012Shapiro, Hemphill, and Otterbacher
  24. CONTACT US• Matt Shapiro (mshapir2@iit.edu)• Libby Hemphill (libby.hemphill@iit.edu)• Jahna Otterbacher (jotterba@iit.edu)Illinois Institute of Technologyinfo@casmlab.orghttp://www.casmlab.org/projects/publicofficials/April 12, 2012Shapiro, Hemphill, and Otterbacher
  25. SUPPLEMENTALSLIDESApril 12, 2012Shapiro, Hemphill, and Otterbacher
  26. WHAT DIDWE EXPECTTO SEE?April 12, 2012Shapiro, Hemphill, and Otterbacher
  27. HYPOTHESESH1. Twitter is a virtual echo chamber in which officials interact mainly with themselves and create homophilous networks.H2. A member of Congress’s location in the network is significantly predicted by both Twitter-based and non-Twitter- based characteristics.H3. The degree to which members of Congress are followed and befriended is a positive function of positioning and pro-social statements via Twitter and polarizing voting records.H4. Polarizing voting records are particularly reflected by positioning and pro-social statements via Twitter.April 12, 2012Shapiro, Hemphill, and Otterbacher
  28. RESULTSHypothesis Supported?Positioning and pro-social Yestweets predictfollowers/friendsPositioning and pro-social Yestweets predict votingrecordsApril 12, 2012Shapiro, Hemphill, and Otterbacher

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