• DocumentCode
    592150
  • Title

    Analyzing Voting Behavior in Italian Parliament: Group Cohesion and Evolution

  • Author

    Amelio, Alessia ; Pizzuti, Clara

  • Author_Institution
    ICAR, Univ. della Calabria, Rende, Italy
  • fYear
    2012
  • fDate
    26-29 Aug. 2012
  • Firstpage
    140
  • Lastpage
    146
  • Abstract
    The roll calls of the Italian Parliament in the current legislature is studied by employing multidimensional scaling, hierarchical clustering, and network analysis. In order to detect changes in voting behavior, the roll calls have been divided in seven periods of six months each. All the methods employed pointed out an increasing fragmentation of the political parties endorsing the previous government that culminated in its downfall. By using the concept of modularity at different resolution levels, we identify the community structure of Parliament and its evolution in each of the time periods considered. The analysis performed revealed as a valuable tool in detecting trends and drifts of Parliamentarians. It showed its effectiveness at identifying political parties and at providing insights on the temporal evolution of groups and their cohesiveness, without having at disposal any knowledge about political membership of Representatives.
  • Keywords
    behavioural sciences computing; data mining; government data processing; pattern clustering; Italian Parliament; data mining; group cohesion; group evolution; hierarchical clustering; modularity concept; multidimensional scaling; network analysis; political membership; political parties; voting behavior analysis; voting behavior change detection; Communities; Government; Indexes; Market research; Matrix decomposition; Singular value decomposition; SVD; hierachical clustering; network evolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4673-2497-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2012.33
  • Filename
    6425771