Tweetcred: Real-time credibility assessment of content on twitter

Aditi Gupta, Ponnurangam Kumaraguru, Carlos Castillo, Patrick Meier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

112 Citations (Scopus)

Abstract

During sudden onset crisis events, the presence of spam, rumors and fake content on Twitter reduces the value of information contained on its messages (or "tweets"). A possible solution to this problem is to use machine learning to automatically evaluate the credibility of a tweet, i.e. whether a person would deem the tweet believable or trustworthy. This has been often framed and studied as a supervised classification problem in an off-line (post-hoc) setting. In this paper, we present a semi-supervised ranking model for scoring tweets according to their credibility. This model is used in TweetCred, a real-time system that assigns a credibility score to tweets in a user’s timeline. TweetCred, available as a browser plug-in, was installed and used by 1,127 Twitter users within a span of three months. During this period, the credibility score for about 5.4 million tweets was computed, allowing us to evaluate TweetCred in terms of response time, effectiveness and usability. To the best of our knowledge, this is the first research work to develop a real-time system for credibility on Twitter, and to evaluate it on a user base of this size.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages228-243
Number of pages16
Volume8851
ISBN (Print)9783319137339
Publication statusPublished - 1 Jan 2014
Event6th International Conference on Social Informatics, SocInfo 2014 - Barcelona, Spain
Duration: 11 Nov 201413 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8851
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Social Informatics, SocInfo 2014
CountrySpain
CityBarcelona
Period11/11/1413/11/14

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Gupta, A., Kumaraguru, P., Castillo, C., & Meier, P. (2014). Tweetcred: Real-time credibility assessment of content on twitter. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8851, pp. 228-243). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8851). Springer Verlag.