Topic Signatures in Political Campaign Speeches

Clément Gautrais 1, 2 Peggy Cellier 3, 4 René Quiniou 2 Alexandre Termier 2, 1
1 UR1 - Université de Rennes 1
2 LACODAM - Large Scale Collaborative Data Mining
Inria Rennes – Bretagne Atlantique , IRISA_D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
3 INSA - Institut National des Sciences Appliquées
4 LIS - Logical Information Systems
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Highlighting the recurrence of topics usage in candidates speeches is a key feature to identify the main ideas of each candidate during a political campaign. In this paper, we present a method combining standard topic modeling with signature mining for analyzing topic recurrence in speeches of Clinton and Trump during the 2016 American presidential campaign. The results show that the method extracts automatically the main ideas of each candidate and, in addition, provides information about the evolution of these topics during the campaign.
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Communication dans un congrès
EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Sep 2017, Copenhagen, Denmark. 2017, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
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Contributeur : Alexandre Termier <>
Soumis le : lundi 20 novembre 2017 - 17:51:15
Dernière modification le : mercredi 16 mai 2018 - 11:24:14
Document(s) archivé(s) le : mercredi 21 février 2018 - 16:06:10

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Clément Gautrais, Peggy Cellier, René Quiniou, Alexandre Termier. Topic Signatures in Political Campaign Speeches. EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Sep 2017, Copenhagen, Denmark. 2017, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 〈hal-01640498〉

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