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Political Research Exchange - PRX

Voting Advice Applications and Social Computing: VAAs as Driving Force and Mirror of Social Change

Elections
 
Voting
 
Methods
 
Panel Number
P457
Panel Chair
Vasiliki (Vicky) Triga
Cyprus University of Technology
Panel Co-Chair
Stefan Marschall
Heinrich-Heine-Universität Düsseldorf
Panel Discussant
Stefan Marschall
Heinrich-Heine-Universität Düsseldorf

Time
08/09/2017 14:00 - 15:40
Location
Building: BL11 Harriet Holters hus Floor: 3 Room: HH 301
Abstract
The panel aims to attract interdisciplinary papers on social computing aspects of VAAs. VAAs can generate new kinds of data on an unprecedented scale to reveal patterns of individual and group behaviour. This much has already been established by the nascent VAA literature. However, apart from a few notable examples, the field has been largely dominated by electoral studies approaches. While this has been a wholly positive development, the frontiers of what can be done remain relatively unexplored, especially from more interdisciplinary perspectives. To name but a few frontier domains, further developments involving massive online randomised experimentation, social network analysis, machine learning and the application of data mining techniques are ripe for exploitation. Such analyses may provide insights on broader questions of social change, such as the promotion of political participation, the use of social vote recommendation processes, the implementation of automated ‘unbiased’ methods of selecting policy issues as well as estimating parties’ positions on the respective issues, etc. To this end, the aim of this panel is to bring together social scientists with an interest in computer science and socially literate computer scientists to explore how the interdisciplinary methodologies and techniques of computational social science can be applied to VAA generated data on the one hand, and how this may contribute to social change on the other hand.

Paper List


Title Details
Different Technologies, same Assumptions? Comparing the Response Behaviour (and Political Stance) of Mobile versus Desktop VAA users View Paper Details
Imputation of User Generated Data View Paper Details
Matching Voters with Parties: A Social Computing Perspective View Paper Details
Measuring Social Attitudes with Voter Advice Application Data View Paper Details
Voting Intention: 'I Prefer not to Say' Versus 'I am Undecided' View Paper Details
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