Health-related rumour detection on Twitter

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)

Abstract

In the last years social networks have emerged as a critical mean for information spreading. In spite of all the positive consequences this phenomenon brings, unverified and instrumentally relevant information statements in circulation, named as rumours, are becoming a potential threat to the society. Recently, there have been several studies on topic-independent rumour detection on Twitter. In this paper we present a novel rumour detection system which focuses on a specific topic, that is health-related rumours on Twitter. To this aim, we constructed a new subset of features including influence potential and network characteristics features. We tested our approach on a real dataset observing promising results, as it is able to correctly detect about 89% of rumours, with acceptable levels of precision.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
PublisherInstitute of Electrical and Electronics Engineers
Pages1599-1606
Number of pages8
Volume2017-January
ISBN (Electronic)9781509030491
DOIs
Publication statusPublished - 15 Dec 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2017) - Kansas City, United States
Duration: 13 Nov 201716 Nov 2017

Conference

Conference2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2017)
Abbreviated titleBIBM 2017
CountryUnited States
CityKansas City
Period13/11/1716/11/17

Keywords

  • Health rumour detection
  • Network- and User-based Features
  • Social microblog
  • Twitter

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  • Cite this

    Sicilia, R., Giudice, S. L., Pei, Y., Pechenizkiy, M., & Soda, P. (2017). Health-related rumour detection on Twitter. In Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (Vol. 2017-January, pp. 1599-1606). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BIBM.2017.8217899