Topic Signatures in Political Campaign Speeches

Clément Gautrais, Peggy Cellier, René Quiniou, Alexandre Termier


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.
Anthology ID:
D17-1249
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2342–2347
Language:
URL:
https://www.aclweb.org/anthology/D17-1249
DOI:
10.18653/v1/D17-1249
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PDF:
http://aclanthology.lst.uni-saarland.de/D17-1249.pdf