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Jang Hyun Kim jhk7@buffalo George A. Barnett gbarnett@buffalo Andrew Gianni

Examining the Structure and Influence of the U.S. Senate’s Hyperlink Network on Roll Call Voting Patterns. Jang Hyun Kim jhk7@buffalo.edu George A. Barnett gbarnett@buffalo.edu Andrew Gianni agianni@buffalo.edu Department of Communication State University of New York at Buffalo May 2007.

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Jang Hyun Kim jhk7@buffalo George A. Barnett gbarnett@buffalo Andrew Gianni

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  1. Examining the Structure and Influence of the U.S. Senate’s Hyperlink Network on Roll Call Voting Patterns Jang Hyun Kim jhk7@buffalo.edu George A. Barnett gbarnett@buffalo.edu Andrew Gianni agianni@buffalo.edu Department of Communication State University of New York at Buffalo May 2007

  2. Hyperlinks • Technical interface: Hyperlink facilitates multi-directional information flow • Social relations: Hypertext linkages embedded in the web are used to establish political affiliations among actors in the context of online political communication

  3. Theoretical Status of Hyperlink Network Social network

  4. Comparing Networks

  5. Political Communicationon the Internet • Hyperlink: - promotes users to share, comment & discuss political information - lowers cost of exchanging political opinions - represents interaction among political actors (politicians) - denotes credibility & reputation of the web site & its owner

  6. Hyperlink Networks • Hyperlinking involves two directions: inward and outward. • Incoming links can be counted by number of hyperlinks received by web page. Number of incoming links represents the prestige of the web page • Linking to a central or popular web page is a way of attracting users

  7. Political Hyperlink Networks Study examines the political/organizational communication structure by analyzing the U.S. Senate web sites in terms of - Hyperlink structure - Description and prediction of centralities in the structure - Campaign financing network - Roll call voting as an outcome of senators’ congressional activity

  8. Method & Data Network Analysis Procedures Data Collection Political Hyperlinks Campaign Financing Data Roll Call Voting Data

  9. Social Network Analysis • Network analysis has been used to study the relations among political actors on the web (Park, 2002; Park et al., 2000, 2002, 2005) • Centrality measures: Degree centrality (Freeman, 1979) Eigenvector centrality (Bonacich, 1972) Closeness centrality (Richards, 1994) Betweenness centrality (Freeman, 1979) • Quadratic Assessment Procedures (QAP) correlation & regression coefficients (UCINET 6-- Borgatti, Everett, & Freeman, 2002; Krackhardt & Porter, 1986)

  10. Hyperlink Data • Hyperlinks obtained with a simple search algorithm using AltavstaTM host:xxx.aaaaaa.xxx and link:xxx.bbbbbb.xxx • The algorithm searches in Senator i’s web site (xxx.aaaaaa.xxx) for links to Senator j’s web site (xxx.bbbbbb.xxx).

  11. Campaign Financing Data • Campaign Financing Data from U.S. Federal Elections Commission http://www.fec.gov/finance/disclosure/ftpdet.shtml • Donations to Senate Campaign for their last election (2000, 2002 or 2004) from 3,766 Political Action Committees (PACs) • Donations to Senate Campaign ONLY • Matrix pre-multiplied by transpose to create a 100 X 100 matrix of senators sij = shared contributions from same PACs

  12. Roll Call Voting Data • Roll Call Voting Data for 109th congress (2005-2006) from http://www.senate.gov/legislative/LIS/roll_call_lists • Recoded to form a 100 by 100 matrix of senators; sij = shared votes

  13. Results Hyperlink Network Campaign Financing Network Shared Voting Network Correlations among Networks Regression Predicting Shared Voting

  14. Hyperlink Structure 14

  15. Hyperlink Results • No clear separation by political party • Democratic party members more central • Democrats use the web for networking purposes

  16. Hyperlink Centrality • 10 most central nodes (Degree Centrality): • Dianne Feinstein (D, CA) • Patrick J. Leahy (D, VT) • Mary L. Landrieu (D, LA) • Olympia J. Snowe (R, ME) • Barbara Boxer (D, CA) • Hillary R. Clinton (D, NY) • Harry Reid (D, NV) • Chuck Grassley (R, IA) • Pete V. Domenici (R, NM) • Charles E. Schumer (D, NY) • Seven of the ten are Democrats, which indicates that Democrats are more central considering direct and indirect linkage.

  17. Campaign Financing Network

  18. Campaign Financing Network • Clear separation by political party • Many links (lots of money) from common donors • Graphic represents strong ties only (greater than the mean shared contribution)

  19. Voting Network Bipartite network Democrats (blue) Vs. Republicans (red)

  20. QAP Correlations among Networks 1 2 3 4 1. Vote 1.0 2. Party .877* 1.0 3. Campaign Funding .163* .134* 1.0 4. Hyperlinks .070* .038 .025 1.0 * p < .000

  21. QAP RegressionPredicting Shared Voting R2 p # of Obs ---------------------------- 0.773 0.000 9890 b β p ------------------------------------------- Intercept 414.608450 0.000000 1.000 Campaign Funding 11.663039 0.045275 0.042 Hyperlinks 0.159105 0.035196 0.005 Political Party 223.250323 0.870118 0.000

  22. Regression Model Hyperlinks Political Party Voting Campaign Funding Β =.035 p =.003 R2=.773 r=.033 r=.038 Β=.870 p=.000 r=.134 Β=.045 p=.039

  23. Discussion • Hyperlink structure is dominated by Democrats • Hyperlink network is a significant predictor of Voting Similarity independent of Political Party • Campaign Financing Network & Political Party are also significant predictors of voting patterns

  24. Future Research • Separate Hyperlink Network by specific issue categories • Determine relationship between the Issue Network and Roll Call Voting on the specific issues to parse out the role of information flows on voting

  25. Issue Categories • A pilot study on 30 sites established the following issue categories

  26. Shared-Issue Network 26

  27. Shared-Issue Network • Republican-centered network • Republicans use the web mainly for issue-debate purpose • Some Democrats use the web for linking to major issue-oriented senators

  28. Issue Centrality • Chuck Grassley (R, IA), • Kay Bailey Hutchinson (TX, R), • Trent Lott (R, MS), • Jim DeMint (R, SC), • Rick Santorum (R, PA) • Conrad Burns (R, MT) • All are Republicans • However, the eigenvector centrality of some actors (mainly Democrats), located in mid-periphery or periphery, are generally higher than the central ones: Hillary Clinton (D, NY) Patrick Leahy (D, VT), Barbara Boxer (D, CA) Dianne Feinstein (D, CA) Joseph Lieberman(D, CT) Charles Schumer (D, NY)

  29. Addressed Issues • Salient issues • Education (79) • Economy (75) • Security & Defense (73) • Health Care & Medicine (70) • Veterans & military (61) • Least addressed issues • Women (8) • Community & rural (12) • Arms & Guns (14) • The Constitution & Second Amendment (14) • Native Americans & Hawaiians (14)

  30. Future Research • Examine four classes of spending tracked by FEC: • cash donations • in kind donations • direct PAC spending in support of a candidate (usually media time) • direct spending by PACs against a candidate • This research looked at first two combined

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