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Identifying trends in information security and privacy concern research

  • Autores: Maor Weinberger, Dan Bouhnik
  • Localización: IFLA journal, ISSN 0340-0352, Vol. 49, Nº. 3, 2023, págs. 527-540
  • Idioma: inglés
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  • Resumen
    • Text mining is a research method that can be used to detect research trends and developments in various fields. In this study, an automated textual analysis tool (Voyant Tools) is applied to a vast corpus of academic papers to identify research trends in the fields of information security and privacy concern, focusing on the differences between the first two decades of the twenty-first century. Furthermore, the conceptual proximity between the related terms ‘information security’ and ‘privacy concern’ is investigated by identifying textual trends. We discovered that, while the first decade of information security research was not entirely defined, the second decade focused on privacy-related issues. The focus of privacy concern research was on commerce and marketing in the first decade and on the social dimension in the second decade. This study supports the use of textual analysis of academic literature to identify research trends in various fields, including technological fields.


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