Other topics you may also agree or disagree: Modeling inter-topic preferences using tweets and matrix factorization

Akira Sasaki, Kazuaki Hanawa, Naoaki Okazaki, Kentaro Inui

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

We present in this paper our approach for modeling inter-topic preferences of Twitter users: for example, those who agree with the Trans-Pacific Partnership (TPP) also agree with free trade. This kind of knowledge is useful not only for stance detection across multiple topics but also for various real-world applications including public opinion surveys, electoral predictions, electoral campaigns, and online debates. In order to extract users' preferences on Twitter, we design linguistic patterns in which people agree and disagree about specific topics (e.g., "A is completely wrong"). By applying these linguistic patterns to a collection of tweets, we extract statements agreeing and disagreeing with various topics. Inspired by previous work on item recommendation, we formalize the task of modeling inter-topic preferences as matrix factorization: representing users' preferences as a user-topic matrix and mapping both users and topics onto a latent feature space that abstracts the preferences. Our experimental results demonstrate both that our proposed approach is useful in predicting missing preferences of users and that the latent vector representations of topics successfully encode inter-topic preferences.

本文言語English
ホスト出版物のタイトルACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
出版社Association for Computational Linguistics (ACL)
ページ398-408
ページ数11
ISBN(電子版)9781945626753
DOI
出版ステータスPublished - 2017
イベント55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada
継続期間: 2017 7月 302017 8月 4

出版物シリーズ

名前ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
1

Other

Other55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
国/地域Canada
CityVancouver
Period17/7/3017/8/4

ASJC Scopus subject areas

  • 言語および言語学
  • 人工知能
  • ソフトウェア
  • 言語学および言語

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