Detecting rumors in social media: A survey

Samah M. Alzanin, Aqil M. Azmi

Research output: Contribution to journalConference articlepeer-review

55 Scopus citations

Abstract

With recent development of technology, especially mobile devices has made the social networks accessible 24/7. Information spreading has become faster than ever, regardless of the credibility of this information. This brings unparalleled challenges in ensuring the reliability of the information. Misinformation spreading has a strong relation especially in the context of breaking news, where the information released gradual, often starting as unverified information. Automatically identifying rumors from online social media especially micro-blogging websites is an important research. Recent research in detecting rumors automatically on social networks have addressed many languages. In this article, we provide an overview of the research into rumors detection in social media which we divided into three groups: supervised based approaches, unsupervised based approaches, and hybrid approaches based on the type of the machine learning used in each approach.

Original languageEnglish
Pages (from-to)294-300
Number of pages7
JournalProcedia Computer Science
Volume142
DOIs
StatePublished - 2018
Externally publishedYes
Event4th Arabic Computational Linguistics, ACLing 2018 - Dubai, United Arab Emirates
Duration: 17 Nov 201819 Nov 2018

Keywords

  • Machine learning
  • Misinformation
  • Rumour detection
  • Social media
  • Survey

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