• DocumentCode
    180693
  • Title

    Exploiting VAA-Generated Data to Identify Policy Dimensions: The Case of England

  • Author

    Wheatley, Jonathan

  • Author_Institution
    Zentrum fuer Demokratie Aarau (ZDA), Aarau, Switzerland
  • fYear
    2014
  • fDate
    6-7 Nov. 2014
  • Firstpage
    118
  • Lastpage
    123
  • Abstract
    Political scientists often talk about "ideological dimensions" that aggregate related policy issues into a single latent construct. Typical examples of ideological dimensions are (economic) Left versus Right and (socially) liberal versus conservative. In this paper I show how individual issues may be aggregated into three ideological dimensions in England by drawing from opinion data derived from the EUvox Voting Advice Application launched shortly before the May 2014 elections to the European Parliament. I go on to map the positions of party supporters with respect to the dimensions I identify. Unlike many other studies of dimensionality, the dimensions are not defined a priori, but are generated inductively from the opinion data using a combination of Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Mokken Scale Analysis. The results suggest that a cultural dimension that measures the degree of openness to outside influences such as the EU and immigration better distinguishes the main political parties in England than the traditional (economic) Left-Right dimension.
  • Keywords
    politics; recommender systems; CFA; EFA; EU; EUvox Voting Advice Application; England; European Parliament; Mokken scale analysis; VAA-generated data; confirmatory factor analysis; cultural dimension; economic dimension; exploratory factor analysis; ideological dimensions; immigration; inductively generated dimensions; latent construct; left-versus-right dimension; liberal-versus-conservative dimension; openness degree measurement; opinion data; party supporter positions; policy dimension identification; political parties; social dimension; Cultural differences; Economics; Eigenvalues and eigenfunctions; Europe; Load modeling; Loading; Nominations and elections; Confirmatory Factor Analysis; Exploratory Factor Analysis; Mokken Scale Analysis; ideological dimensions; parties;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic and Social Media Adaptation and Personalization (SMAP), 2014 9th International Workshop on
  • Conference_Location
    Corfu
  • Print_ISBN
    978-1-4799-6813-8
  • Type

    conf

  • DOI
    10.1109/SMAP.2014.16
  • Filename
    6978965