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User Privacy, Surveillance and Public Health during COVID-19 – An Examination of Twitterverse

  • Paras Bhatt
  • , Naga Vemprala
  • , Rohit Valecha
  • , Govind Hariharan
  • , H. Raghav Rao
  • University of Texas at San Antonio
  • University of Portland
  • Kennesaw State University

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Online users frequently rely on social networking platforms to transmit public concerns and raise awareness about societal issues. With many government organizations actively employing social media data in recent times, the need for processing public concerns on social media has become a critical topic of interest across academic scholars and practitioners. However, the growing volume of social media data makes it difficult to process all the issues under a single umbrella, causing to overlook the main topic of interest within communication technologies, such as privacy. For example, during the COVID-19 pandemic, arguments on privacy and health issues exploded on Twitter, with several threads centered on contact tracking, health data gathering, and its usage by government agencies. To address the challenges of rising data volumes and to understand the importance of privacy concerns, particularly among users seeking greater privacy protection during this pandemic, we conduct a focused empirical analysis of user tweets about privacy. In this two-part research, our first study reveals three macro privacy issues of discussion distilled from the Twitter corpus, subsequently subdivided into 12 user privacy categories. The second study builds on the findings of the first study, focusing on the primary difficulties highlighted in the macro privacy subjects—contact tracing and digital surveillance. Using a document clustering approach, we present implications for the focal privacy topics that policymakers, agencies, and governments should consider for offering better privacy protections and help the community rebuild.

Original languageEnglish
Pages (from-to)1667-1682
Number of pages16
JournalInformation Systems Frontiers
Volume25
Issue number5
DOIs
StatePublished - Oct 2023

Keywords

  • COVID-19
  • Coronavirus
  • Hierarchical clustering
  • Privacy
  • Social Media
  • Text mining

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