Suspicious news detection using micro blog text

Tsubasa Tagami, Hiroki Ouchi, Hiroki Asano, Kazuaki Hanawa, Kaori Uchiyama, Kaito Suzuki, Kentaro Inui, Atsushi Komiya, Atsuo Fujimura, Hitofumi Yanai, Ryo Yamashita, Akinori MacHino

研究成果: Paper査読

1 被引用数 (Scopus)

抄録

We present a new task, suspicious news detection using micro blog text. This task aimsto support human experts to detect suspiciousnews articles to be verified, which is costly buta crucial step before verifying the truthfulnessof the articles. Specifically, in this task, givena set of posts on SNS referring to a news article, the goal is to judge whether the articleis suspicious or not. For this task, we create apublicly available dataset in Japanese and provide benchmark results by using several basic machine learning techniques. Experimental results show that our models can reduce thecost of manual fact-checking process.

本文言語English
ページ648-657
ページ数10
出版ステータスPublished - 2018
イベント32nd Pacific Asia Conference on Language, Information and Computation, PACLIC 2018 - Hong Kong, Hong Kong
継続期間: 2018 12月 12018 12月 3

Conference

Conference32nd Pacific Asia Conference on Language, Information and Computation, PACLIC 2018
国/地域Hong Kong
CityHong Kong
Period18/12/118/12/3

ASJC Scopus subject areas

  • 言語および言語学
  • コンピュータ サイエンス(その他)

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