Fake News Detection in Twitter

Authors

  • Ainab Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidri, India
  • Megha D. Hegde Assistant Professor, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidri, India
  • S. Akash Kumar Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidri, India
  • Dhanush Shetty Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidri, India
  • M. S. Venkata Chandrashekar Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidri, India

Keywords:

Media focus, Prioritization, Temporal prevalence, User attention

Abstract

Mass media sources, specifically the news media, have traditionally informed us of quotidian events. In modern times, social media services such as Twitter provide an extensive amount of user-generated data, which have great potential to contain informative news related information. For these resources to be useful, we must find a way to filter noise and only capture the information that, based on its similarity to the news media, is considered prized possessions. To achieve categories, information must be ranked in order of estimated importance considering two factors. First, the temporal widespread of a topic in the news is an element of importance can be considered the media focus of a topic. Second, the temporal prevalence of the topic in social media indicates its user awareness.

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Published

15-08-2020

How to Cite

[1]
Ainab, M. D. Hegde, S. A. Kumar, D. Shetty, and M. S. V. Chandrashekar, “Fake News Detection in Twitter”, IJRESM, vol. 3, no. 8, pp. 257–259, Aug. 2020.

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Articles