ECPR

Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”

ECPR

Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”

Back to Panel Details
Back to Panel Details

Bringing Together VAA Data and Party Research

Elections
Party Manifestos
Political Parties
Voting
Party Systems
P034
Eric Linhart
Technische Universität Chemnitz
Eric Linhart
Technische Universität Chemnitz

Wednesday 13:00 - 14:40 (04/09/2019)

Building: Institute of Geography Floor: 3rd floor Room: 320

Abstract

While the original intention of constructing voting advice applications (VAAs) is the provision of tools that allow voters to compare their policy positions with those of parties and, thus, give them orientation in elections, a further strand of research around VAAs has grown. This strand does not contrast the answers of voters and parties but searches for differences between the various parties. The potential for party and party system research is enormous. A new source for data emerges which allows researchers to estimate which parties are close or distant to each other, in which policy fields parties do or do not share similar positions, how party systems are structured, and much more. At the same time, there might be concerns that data which has originally been collected for other purposes could be inappropriate for the analysis of parties and party systems. This panel includes papers which theoretically discuss the viability of VAA data for party research and/or apply VAA data empirically in order to contribute to questions as sketched above.

Title Details
Differences of Political Positions within Parties: The 2017 Elections in Liechtenstein View Paper Details
Party Coherence and Polarisation in Multi-Level Systems – Analysing Swiss Parties Based on VAA Data View Paper Details
Measuring Party System Polarisation with Voting Advice Application Data View Paper Details