A first step towards combating fake news over online social media

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

3 Scopus citations

Abstract

Fake news has recently leveraged the power and scale of online social media to effectively spread misinformation which not only erodes the trust of people on traditional presses and journalisms, but also manipulates the opinions and sentiments of the public. Detecting fake news is a daunting challenge due to subtle difference between real and fake news. As a first step of fighting with fake news, this paper characterizes hundreds of popular fake and real news measured by shares, reactions, and comments on Facebook from two perspectives: Web sites and content. Our site analysis reveals that the Web sites of the fake and real news publishers exhibit diverse registration behaviors and registration timing. In addition, fake news tends to disappear from the Web after a certain amount of time. The content characterizations on the fake and real news corpus suggest that simply applying term frequency - inverse document frequency (tf-idf) and Latent Dirichlet allocation (LDA) topic modeling is inefficient in detecting fake news, while exploring document similarity with the term and word vectors is a very promising direction for predicting fake and real news. To the best of our knowledge, this is the first effort to systematically study the Web sites and content characteristics of fake and real news, which will provide key insights for effectively detecting fake news on social media.

Original languageEnglish (US)
Title of host publicationWireless Algorithms, Systems, and Applications - 13th International Conference, WASA 2018, Proceedings
PublisherSpringer Verlag
Pages521-531
Number of pages11
ISBN (Print)9783319942674
DOIs
Publication statusPublished - Jan 1 2018
Event13th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2018 - Tianjin, China
Duration: Jun 20 2018Jun 22 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10874 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2018
CountryChina
CityTianjin
Period6/20/186/22/18

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Xu, K., Wang, F., Wang, H., & Yang, B. (2018). A first step towards combating fake news over online social media. In Wireless Algorithms, Systems, and Applications - 13th International Conference, WASA 2018, Proceedings (pp. 521-531). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10874 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-94268-1_43