Abstract

For the fifth edition of the workshop on Mining Actionable Insights from Social Networks (MAISoN), we organized a special edition with focus on dis/misinformation mining from social media, co-located with CIKM 2020. This topic has attracted a lot of interest from the community since the Coronavirus (COVID-19) epidemic has given rise to an increase of misinformation on social media. The aim of this edition was to bring together researchers from different disciplines interested in mining dis/misinformation on social media. In particular, the distinguishing focus of this special edition was its emphasis on techniques that use social media data for building diagnostic, predictive and prescriptive analysis models related to misinformation. This means that there is rigorous attention for techniques that can be used to understand how and why dis/misinformation is created and spread, to uncover hidden and unexpected aspects of dis/misinformation content, and to recommend insightful countermeasures to restrict the circulation of dis/misinformation and alleviate their negative effects.

Original languageEnglish (US)
Title of host publicationCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages3527-3528
Number of pages2
ISBN (Electronic)9781450368599
DOIs
StatePublished - Oct 19 2020
Event29th ACM International Conference on Information and Knowledge Management, CIKM 2020 - Virtual, Online, Ireland
Duration: Oct 19 2020Oct 23 2020

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference29th ACM International Conference on Information and Knowledge Management, CIKM 2020
Country/TerritoryIreland
CityVirtual, Online
Period10/19/2010/23/20

Keywords

  • disinformation
  • domain insights
  • misinformation
  • predictive modelling
  • prescriptive modeling
  • social media

ASJC Scopus subject areas

  • General Business, Management and Accounting
  • General Decision Sciences

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