Chapter

Active Media Technology

Volume 8610 of the series Lecture Notes in Computer Science pp 96-109

Mining False Information on Twitter for a Major Disaster Situation

  • Keita NabeshimaAffiliated withGraduate School of Information Sciences, Tohoku University / Miyagi
  • , Junta MizunoAffiliated withResilient ICT Research Center, NICT / Miyagi
  • , Naoaki OkazakiAffiliated withGraduate School of Information Sciences, Tohoku University / MiyagiJapan Science and Technology Agency (JST) / Tokyo
  • , Kentaro InuiAffiliated withGraduate School of Information Sciences, Tohoku University / Miyagi

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Abstract

Social networking services (SNS), such as Twitter, disseminate not only useful information, but also false information. Identifying this false information is crucial in order to keep the information on a SNS reliable. The aim of this paper is to develop a method of extracting false information from among a large collection of tweets. We do so by using a set of linguistic patterns formulated to correct false information. More specifically, the proposed method extracts text passages that match specified correction patterns, clusters the passages into topics of false information, and selects a passage that represents each topic of false information. In the experiment we conduct, we build an evaluation set manually, and demonstrate the effectiveness of the proposed method.