Making Computers Understand Coalition and Opposition in Parliamentary Democracy - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Making Computers Understand Coalition and Opposition in Parliamentary Democracy

Résumé

In recent years a tremendous raise in the establishment of Open Data initiatives can be observed, aiming at more transparency in government and public institutions. One facet of this trend are data from legislative bodies, including records and archived transcripts of plenary sessions as a measure of transparency and accountability. In this paper the system design and a prototypical implementation of an information system that makes use of these data is presented. From session transcripts naive metrics such as when and how often representatives participate in political discourse but also network metrics as in with whom representatives engage in consenting and opposing discourse can be derived. The objective of the system is to make those relationships visible and accessible to the user in an intuitive way. The system neither can nor attempts to interpret the data, this is left to the user. This paper discusses how data analytics, data visualisation, and network analytics can be facilitated to make the transcripts of legislative bodies more accessible for this purpose. The findings are underpinned by first observations over a proof-of-concept prototype which exploits data available from the Austrian parliament.
Fichier principal
Vignette du fichier
430312_1_En_21_Chapter.pdf (1.39 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01636449 , version 1 (16-11-2017)

Licence

Paternité

Identifiants

Citer

Matthias Steinbauer, Markus Hiesmair, Gabriele Anderst-Kotsis. Making Computers Understand Coalition and Opposition in Parliamentary Democracy. 5th International Conference on Electronic Government and the Information Systems Perspective (EGOV)), Sep 2016, Porto, Portugal. pp.265-276, ⟨10.1007/978-3-319-44421-5_21⟩. ⟨hal-01636449⟩
119 Consultations
96 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More