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Information credibility on twitter

Published: 28 March 2011 Publication History

Abstract

We analyze the information credibility of news propagated through Twitter, a popular microblogging service. Previous research has shown that most of the messages posted on Twitter are truthful, but the service is also used to spread misinformation and false rumors, often unintentionally.
On this paper we focus on automatic methods for assessing the credibility of a given set of tweets. Specifically, we analyze microblog postings related to "trending" topics, and classify them as credible or not credible, based on features extracted from them. We use features from users' posting and re-posting ("re-tweeting") behavior, from the text of the posts, and from citations to external sources.
We evaluate our methods using a significant number of human assessments about the credibility of items on a recent sample of Twitter postings. Our results shows that there are measurable differences in the way messages propagate, that can be used to classify them automatically as credible or not credible, with precision and recall in the range of 70% to 80%.

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cover image ACM Other conferences
WWW '11: Proceedings of the 20th international conference on World wide web
March 2011
840 pages
ISBN:9781450306324
DOI:10.1145/1963405
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 28 March 2011

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Author Tags

  1. social media analytics
  2. social media credibility
  3. twitter

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WWW '11
WWW '11: 20th International World Wide Web Conference
March 28 - April 1, 2011
Hyderabad, India

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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  • (2025)A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated TextsIEEE Access10.1109/ACCESS.2025.353880513(25301-25324)Online publication date: 2025
  • (2025)Rumor Propagation and Detection Techniques in Social NetworksITM Web of Conferences10.1051/itmconf/2025730201073(02010)Online publication date: 17-Feb-2025
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