jang hyun kim jhk7@buffalo george a. barnett gbarnett@buffalo andrew gianni
DESCRIPTION
Examining the Structure and Influence of the U.S. Senate’s Hyperlink Network on Roll Call Voting Patterns. Jang Hyun Kim [email protected] George A. Barnett [email protected] Andrew Gianni [email protected] Department of Communication State University of New York at Buffalo May 2007. - PowerPoint PPT PresentationTRANSCRIPT
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Examining the Structure and Influence of the U.S. Senate’s
Hyperlink Network on Roll Call Voting Patterns
Jang Hyun [email protected]
George A. [email protected]
Andrew [email protected]
Department of Communication
State University of New York at Buffalo
May 2007
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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
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Theoretical Status of Hyperlink Network
Communication network
Mediated-network
Computer-mediated network
Internet network
Hyperlink network
Social network
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Comparing NetworksType Relational Content Analysis Unit
Social network Any social relations Individual, group, organization or state
Communication network
Communication or information
Individual, group,
Organization or state
Mediated network Communication, information, feedback
Individual, group or channel
Computer-mediated
network
Computer mediated Communication
Individual, group or
computer systems
Internet network Internet mediated
Communication
Individual, group,
Listserv or Usenet
Hyperlink network Hyperlink mediated Communication
Individual, group or
web sites
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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
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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
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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
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Method & Data
•Network Analysis Procedures
•Data Collection
–Political Hyperlinks
–Campaign Financing Data
–Roll Call Voting Data
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Social Network Analysis• Network analysis has been used to study the relati
ons 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)
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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).
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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
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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
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Results
1. Hyperlink Network
2. Campaign Financing Network
3. Shared Voting Network
4. Correlations among Networks
5. Regression Predicting Shared Voting
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Hyperlink Structure
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Hyperlink Results
• No clear separation by political party
• Democratic party members more central
• Democrats use the web for networking purposes
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Hyperlink Centrality• 10 most central nodes (Degree Centrality):
1. Dianne Feinstein (D, CA) 2. Patrick J. Leahy (D, VT) 3. Mary L. Landrieu (D, LA) 4. Olympia J. Snowe (R, ME) 5. Barbara Boxer (D, CA) 6. Hillary R. Clinton (D, NY) 7. Harry Reid (D, NV) 8. Chuck Grassley (R, IA) 9. Pete V. Domenici (R, NM)10.Charles E. Schumer (D, NY)
• Seven of the ten are Democrats, which indicates that Democrats ar
e more central considering direct and indirect linkage.
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Campaign Financing Network
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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)
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Voting Network
Bipartite network Democrats (blue) Vs. Republicans (red)
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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
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QAP Regression Predicting 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
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Regression Model
Hyperlinks
Political Party Voting
Campaign Funding
Β =.035 p =.003
Β=.870 p=.000
Β=.045 p=.039
r=.038
r=.134
r=.033
R2=.773
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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
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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
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Issue Categories• A pilot study on 30 sites established the following issue
categories1) Agriculture2) Arms & Guns3) Civil Rights, Human Rights & Ju
diciary4) Community & Rural, Urban Affair
s 5) Constitution & The Second Ame
ndment6) Economy, Business, Trade, Avia
tion & Consumers 7) Education8) Environment 9) Women10) Family, Children & Housing 11) Foreign Affairs & Immigration 12) Government & Budget
13) Health Care, Medicare & Drugs14) Homeland Security, Border Security & Defense15) Iraq, Terrorism, War, North Korea, & Middle East 16) Jobs & Labor17) Legislation, Law Enforcement, & Election Reform 18) Localization19) Native American & Hawaiians 20) Taxes 21) Technology & Transportation 22) Veterans & Military23) Water, Forest, & Natural Resources24) Welfare, Social Security & Seniors
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Shared-Issue Network
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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
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Issue Centrality
1. Chuck Grassley (R, IA), 2. Kay Bailey Hutchinson (TX, R), 3. Trent Lott (R, MS), 4. Jim DeMint (R, SC), 5. Rick Santorum (R, PA)6. 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)
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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)
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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