Twitter rumour detection in the health domain

Rosa Sicilia, Stella Lo Giudice, Yulong Pei, Mykola Pechenizkiy, Paolo Soda

Research output: Contribution to journalArticleAcademicpeer-review

72 Citations (Scopus)
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In the last years social networks have emerged as a critical mean for information spreading bringing along several advantages. At the same time, unverified and instrumentally relevant information statements in circulation, named as rumours, are becoming a potential threat to the society. For this reason, although the identification in social microblogs of which topic is a rumour has been studied in several works, there is the need to detect if a post is either a rumor or not. In this paper we cope with this last challenge presenting a novel rumour detection system that leverages on newly designed features, including influence potential and network characteristics measures. We tested our approach on a real dataset composed of health-related posts collected from Twitter microblog. We observe promising results, as the system is able to correctly detect about 90% of rumours, with acceptable levels of precision.

Original languageEnglish
Pages (from-to)33-40
Number of pages8
JournalExpert Systems with Applications
Publication statusPublished - 15 Nov 2018


  • Health rumour detection
  • Network-and user-based features
  • Social microblog
  • Twitter


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