Social media mining under the COVID-19 context: Progress, challenges, and opportunities

Xiao Huang, Siqin Wang, Mengxi Zhang, Tao Hu, Alexander Hohl, Bing She, Xi Gong, Jianxin Li, Xiao Liu, Oliver Gruebner, Regina Liu, Xiao Li, Zhewei Liu, Xinyue Ye, Zhenlong Li

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.

Original languageEnglish (US)
Article number102967
JournalInternational Journal of Applied Earth Observation and Geoinformation
StatePublished - Sep 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Earth-Surface Processes
  • Computers in Earth Sciences
  • Management, Monitoring, Policy and Law


  • Big data
  • COVID-19
  • Data mining
  • Pandemic
  • Social media


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