candidate mapping: finding your place amongst the candidates

Candidate Mapping: Finding Your PlaceAmongst the Candidates

Justin Donaldson and William Hazlewood

Candidate Mapping: Finding Your Place Amongst the Candidates

1 IntroductionSpatial Voting and Policy SpaceMotivation

2 Data and Methodology2008 US Presidential Election DataPolicy Space Methodology

3 Participant StudyStudy OverviewStudy Results

Spatial Voting Theory

Spatial Voting Theory: How do People Choose a Candidate?

Introduced by Anthony Downs in 1957

Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)

Figure: Lewis & King Political Analysis 8:1 1999Candidate Mapping: Finding Your Place Amongst the Candidates

Introduced by Anthony Downs in 1957Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)

Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)

Introduced by Anthony Downs in 1957Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.

“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)

Introduced by Anthony Downs in 1957Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)

Policy Space for Candidates

Candidates have different stanceson a huge variety of issues.

In most cases, the differentvarieties of stances are verylimited (by party platform).

These varieties of stances can becondensed into a relevant “policyspace” by means of dimensionalityreduction.

Figure credit: Poole (Dw-Nominate) and Cahoon (1975)

Do Most Folks Understand “Policy Space”?

1 Most political policy spaces are intrinsically lowdimensional.

2 Some people may think they have a “fuzzy” notion ofwhere they lie on the dominant intrinsic dimension(currently, typically liberal to conservative*), and whichcandidates are “most like” them.

3 How do their “fuzzy” notions match up to their “actualposition” that would be indicated through the use of policyspace?

4 What can we learn about their position error?

5 What demographic trends are present?

Collected data from two independent websites: 2decide.com,and ontheissues.org.

Figure: 2decide.com

Figure: ontheissues.org

Candidate and Issue List

Candidates(As of Oct. 2007)

Hillary Clinton

John Edwards

Rudy Giuliani

Mike Gravel

Mike Huckabee

Dennis Kucinich

John McCain

Barack Obama

Ron Paul

Mitt Romney

IssuesRoe v. Wade

Death Penalty

Education: No Child Left Behind

Embryonic Stem Cells:Legalization of Research

Energy & Oil: Pursue ANWRDrilling

Energy & Oil: Adopt KyotoProtocol

Guns: Assault Weapons Ban

Guns: Background Checks forHandguns

Homeland Security: Patriot Act

Homeland Security: Guantanamo

Homeland Security:Waterboarding (torture)

Issues, Cont.Immigration: Border Fence

Internet Neutrality

Iran: Sanctions

Iran: Military Action as Option

Iraq: Initial Invasion Justified

Iraq: Troop Surge

Iraq: Withdrawal

Minimum Wage Increase

Same-Sex: Marriage

Same-Sex: Civil Union

Same-Sex: Constitutional Ban

Universal Healthcare

Homeland Security: DomesticWiretapping

Immigration: Citizenship Path forIllegals

Processing and Factoring Candidate Data

Candidate responses to issues are ordinally coded to reflect anincreasingly stronger stance on an issue.

Default: Supports < Mixed Opinion < Opposes.

Iraq war withdrawal: Immediate Withdrawal < SupportsPhased Withdrawal < Opposes.

Same sex marriage/union: Supports < Supports butbelieves the issues should be left to the states. < Mixedopinion < Opposes but believes the issue should be left tothe states < Opposes.

Matrix Form

Data Gathered into Matrix FormCandidate Issues

Roe V. Wade Uni. Health Death Penalty ...

Clinton Support Oppose Support ...Edwards Support Support Neither ...Giuliani Support Support Let States Decide ...... ... ... ... ...

Data Processed into Similarities/Dissimilarities withGower Dissimilarity

sijk = 1−|xik − xjk |

rkClinton Edwards Giuliani ...

Clinton N/A 0.3 0.1 ...Edwards 0.3 N/A 0.2 ...Giuliani 0.1 0.2 N/A ...... ... ... ... ...

Matrix Form

Clinton Edwards Giuliani ...Clinton N/A 0.3 0.1 ...Edwards 0.3 N/A 0.2 ...Giuliani 0.1 0.2 N/A ...... ... ... ... ...

Matrix Form

rkClinton Edwards Giuliani ...

Clinton N/A 0.3 0.1 ...Edwards 0.3 N/A 0.2 ...Giuliani 0.1 0.2 N/A ...... ... ... ... ...

Dimensionality Reduction

Sammon mapping was applied to theGower dissimilarity matrix in order toexpress the candidate relationalinformation in two dimensions.

i<j [dij∗]

[dij∗ − dij ]

dij∗

The error of the representation is very low0.011 (∼ 1%), well within error tolerances.

The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani 0 100 200 300 400 500

Sammon Map of Candidate Similarity

Liberal to Conservative

ClintonEdwards_beforeClinton_before

Huckabee

RomneyKucinich McCain

Gravel

GiulianiEdwards

Previous and current positions, Obama’s position in Poole’s analysishttp://voteview.ucsd.edu/Clinton_and_Obama.htm

i<j [dij∗]

[dij∗ − dij ]

dij∗

Huckabee

Gravel

GiulianiEdwards

i<j [dij∗]

[dij∗ − dij ]

dij∗

The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani

0 100 200 300 400 500

Huckabee

Gravel

GiulianiEdwards

i<j [dij∗]

[dij∗ − dij ]

dij∗

Huckabee

Gravel

GiulianiEdwards

i<j [dij∗]

[dij∗ − dij ]

dij∗

Huckabee

Gravel

GiulianiEdwards

Participant Study Details

The web-based study(http://www.candidatemapper2008.net) collected:

1 Consent and DemographicInformation

2 Issue stance information for eachof the 25 issues. (Plus ability toresearch issues.)

3 Brief open ended exit survey

Participant Study Details Cont.

1 The study calculates theparticipant’s position in policyspace along with all the othercandidates.

2 The study presents the resultingmap to the user (with their “real”position hidden) and asks them toindicate where they think they liein the policy space

3 The study reveals the participantsposition, and invites them toexplore the map in more detailand answer exit questions.

Summary Statistics

Focus the analysis on the participants’ political stance (liberal toconservative).

Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.

Unit error distance is given in terms of pixels of the participant studyapplet.

Which policy stance group has the lowest error?

Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)

N mean stddev stderr

vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53

sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83

Summary Statistics

T-test Values Between Political Stance

Are the groups of participant political stances statisticallydifferent in their positioning error?

Table: Pairwise t-test values for participant stances(l=liberal,c=conservative)

vl swl sll n slc swc

sw liberal 0.19sl liberal 0.47 0.99

neither *0.10 0.39 0.50sl consrv. *0.07 0.16 0.19 0.38

sw consrv. *0.10 0.38 0.49 0.96 0.41vy consrv. 0.35 0.40 0.39 0.46 0.63 0.46

T-test Values Between Political Stance

Table: Pairwise t-test values for participant stances(l=liberal,c=conservative)

vl swl sll n slc swc

sw liberal 0.19sl liberal 0.47 0.99

neither *0.10 0.39 0.50sl consrv. *0.07 0.16 0.19 0.38

sw consrv. *0.10 0.38 0.49 0.96 0.41vy consrv. 0.35 0.40 0.39 0.46 0.63 0.46

T-test Values Between Political Stance Cont.

1 2 3 4 5 6 7

Distance Between Selected and Calculated Position

1: Very liberal to 7: Very conservative

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Figure: Mean distance distribution between selected and calculateddistances, by participant political stance.Candidate Mapping: Finding Your Place Amongst the Candidates

Consistency in Error

Do participant stance groups differ consistently in the directionof their error?

very_liberal slightly_liberal somewhat_conservative

Distance Error in X Dimension

General Participant Political Stance (Very Liberal to Very Conservative)

Figure: Difference in x dimension

Distance Error in Y Dimension

Figure: Difference in y dimension

very_liberal slightly_liberal somewhat_conservative−

Figure: Difference in y dimensionCandidate Mapping: Finding Your Place Amongst the Candidates

The Big Picture

Isn’t this a VISUALISATION conference?

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0 100 200 300 400 500

Map of Selected and Calculated (Dimensional Scaled) Positions

Clinton

Huckabee

Gravel

GiulianiEdwards

very_liberalsomewhat_liberalslightly_liberalneitherslightly_conservativesomewhat_conservativevery_conservativen/a

Figure: Position of all participants who provided both their issueposition stances and their indicated position.

The Big Picture

Isn’t this a VISUALISATION conference?

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● ●●●

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0 100 200 300 400 500

Map of Selected and Calculated (Dimensional Scaled) Positions

Clinton

Huckabee

Gravel

GiulianiEdwards

very_liberalsomewhat_liberalslightly_liberalneitherslightly_conservativesomewhat_conservativevery_conservativen/a

Figure: Position of all participants who provided both their issueposition stances and their indicated position.

Conclusions

Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.

Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?

Conclusions

Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).

Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?

Conclusions

Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).

Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?

Conclusions

Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].

Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?

Conclusions

Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).

Questions?

Conclusions

Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?

Discussion

Can candidate mapping be used as a form of voting orpolitical awareness tool?

Can it be used to reduce the effects of political ‘gaming,’such as gerrymandering?

Handling weighted issue policy maps is possible, but verychallenging for global visualization!

candidate mapping: finding your place amongst the candidates

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