Information Extraction From Social Media for Epidemic Models

Tariq Soussan, Marcello Trovati

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Social media platforms are widely used to share opinions, facts, and real-time general information on specific events. This chapter will focus on discussing and presenting data analytics approaches which combine a variety of techniques based on text mining, machine learning, network analysis, and mathematical modelling to assess real-time data extracted from social media and other suitable data related to pandemic outbreaks. The use of real-time insights regarding pandemic outbreaks provides a valuable tool to inform and validate existing modelling techniques and methods. Furthermore, this would also support the discovering process of actionable information to facilitate the decision-making process by enhancing the most informed and appropriate decision, based on the available data. The chapter will also focus on the visualisation and usability of the insight identified during the process to address a non-technical audience.
Original languageEnglish
Title of host publicationData Science Advancements in Pandemic and Outbreak Management
PublisherIGI Global
Number of pages15
ISBN (Print)9781799867364
Publication statusPublished - 22 Mar 2021


  • Social Media Platforms


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