‘Fighting’ or ‘Conflict’? An Approach to Revealing Concepts of Terms in Political Discourse

Linyuan Tang, Kyo Kageura

Abstract
Previous work on the epistemology of fact-checking indicated the dilemma between the needs of binary answers for the public and ambiguity of political discussion. Determining concepts represented by terms in political discourse can be considered as a Word-Sense Disambiguation (WSD) task. The analysis of political discourse, however, requires identifying precise concepts of terms from relatively small data. This work attempts to provide a basic framework for revealing concepts of terms in political discourse with explicit contextual information. The framework consists of three parts: 1) extracting important terms, 2) generating concordance for each term with stipulative definitions and explanations, and 3) agglomerating similar information of the term by hierarchical clustering. Utterances made by Prime Minister Abe Shinzo in the Diet of Japan are used to examine our framework. Importantly, we revealed the conceptual inconsistency of the term Sonritsu-kiki-jitai. The framework was proved to work, but only for a small number of terms due to lack of explicit contextual information.
Anthology ID:
W17-4216
Volume:
Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Octavian Popescu, Carlo Strapparava
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
90–94
Language:
URL:
https://aclanthology.org/W17-4216
DOI:
10.18653/v1/W17-4216
Bibkey:
Cite (ACL):
Linyuan Tang and Kyo Kageura. 2017. ‘Fighting’ or ‘Conflict’? An Approach to Revealing Concepts of Terms in Political Discourse. In Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism, pages 90–94, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
‘Fighting’ or ‘Conflict’? An Approach to Revealing Concepts of Terms in Political Discourse (Tang & Kageura, 2017)
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