Examining the Structure and Influence of the U.S. Senate’s

Hyperlink Network on Roll Call Voting Patterns

Jang Hyun Kimjhk7@buffalo.edu

George A. Barnettgbarnett@buffalo.edu

Andrew Gianniagianni@buffalo.edu

Department of Communication

State University of New York at Buffalo

May 2007

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

Theoretical Status of Hyperlink Network

Communication network

Mediated-network

Computer-mediated network

Internet network

Hyperlink network

Social network

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

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

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

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

Method & Data

•Network Analysis Procedures

•Data Collection

–Political Hyperlinks

–Campaign Financing Data

–Roll Call Voting Data

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)

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).

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

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

Results

1. Hyperlink Network

2. Campaign Financing Network

3. Shared Voting Network

4. Correlations among Networks

5. Regression Predicting Shared Voting

Hyperlink Structure

14

Hyperlink Results

• No clear separation by political party

• Democratic party members more central

• Democrats use the web for networking purposes

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.

Campaign Financing Network

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)

Voting Network

Bipartite network Democrats (blue) Vs. Republicans (red)

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

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

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

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

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

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

Shared-Issue Network

26

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

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)

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)

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