Emotional analysis of safeness and risk perception of cybersecurity attacks during the COVID-19 pandemic

Fabio Garcia, Francesco Borghini, Ekaterina Makshanova Rome, Mara Lombardi, Soodamani Ramalingam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The assessment of perceived safeness and risk by persons is especially valuable for security and safety managing. Each person is founded on the opinion of other people to make a selection and the Internet embodies the place where these opinions are mostly pursued, taken, and estimated. From this point of view, social networks are characterized by a considerable influence. Due to this reason, Opinion Mining and Sentiment Analysis have found outstanding employs in diverse environments and one of the most remarkable is expressed by public security and safety. The purpose of the present work is to investigate the perception of safeness and risk of cybersecurity attacks during COVID-19 pandemic by means of the semantic analysis of the textual contents existing in Twitter.
Original languageEnglish
Title of host publication2022 IEEE International Carnahan Conference on Security Technology (ICCST)
Place of PublicationValeč u Hrotovic, Czech Republic
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
ISBN (Electronic)978-1-6654-9363-5
ISBN (Print)978-1-6654-9364-2
DOIs
Publication statusPublished - 9 Sept 2022
Event2022 IEEE International Carnahan Conference on Security Technology (ICCST) - Valec u Hrotovic, Czech Republic
Duration: 7 Sept 20229 Sept 2022
https://ieeexplore.ieee.org/xpl/conhome/9896399/proceeding

Conference

Conference2022 IEEE International Carnahan Conference on Security Technology (ICCST)
Abbreviated titleICCST 2022
Country/TerritoryCzech Republic
CityValec u Hrotovic
Period7/09/229/09/22
Internet address

Keywords

  • COVID-19 pandemic
  • OSINT
  • Open-Source Intelligent Techniques for security & safety
  • Perceived risk assessment for security & safety
  • cybersecurity
  • opinion mining for security & safety
  • sentiment analysis for security & safety

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