Mining False Information on Twitter for a Major Disaster Situation

  • Keita Nabeshima
  • Junta Mizuno
  • Naoaki Okazaki
  • Kentaro Inui
Conference paper

DOI: 10.1007/978-3-319-09912-5_9

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8610)
Cite this paper as:
Nabeshima K., Mizuno J., Okazaki N., Inui K. (2014) Mining False Information on Twitter for a Major Disaster Situation. In: Ślȩzak D., Schaefer G., Vuong S.T., Kim YS. (eds) Active Media Technology. AMT 2014. Lecture Notes in Computer Science, vol 8610. Springer, Cham

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.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Keita Nabeshima
    • 1
  • Junta Mizuno
    • 2
  • Naoaki Okazaki
    • 1
    • 3
  • Kentaro Inui
    • 1
  1. 1.Graduate School of Information SciencesTohoku University / MiyagiJapan
  2. 2.Resilient ICT Research CenterNICT / MiyagiJapan
  3. 3.Japan Science and Technology Agency (JST) / TokyoJapan

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