Social media and personal health might be a dan-gerous combination: people are influenced by what they read online and don't pay attention to who wrote what they read. What happened during the COVID-19 pandemic? Who were the opinion leaders on social media? What were the conversations about? How did the health institutions communicate? To under-stand this, we focus on Twitter, and we analyze more than three million of Italian-written tweets posted from January 2020 to December 2021. We propose a method to identify opinion leaders and to analyze the content of the conversations. Results show that: (i) opinion leaders are linked to what they say and when they say it; (ii) politicians, newscast, and ordinary people accounts were able to become opinion leaders during the pandemic; (iii) conversations moved from a medical focus (at the beginning of the pandemic) to a social focus (in the last months of 2021); (iv) absence of health care institutions among opinion leaders. These results show that our approach might be useful for those who want to monitor the social scenario in terms of health (e.g., to identify as soon as possible accounts against or critical to medicine or to health authorities).

Opinion Leaders and Twitter: Metric Proposal and Psycholinguistic Analysis / Furini, M.; Flisi, E.. - 2022-:(2022), pp. 1-5. ( 27th IEEE Symposium on Computers and Communications, ISCC 2022 Greece 2022) [10.1109/ISCC55528.2022.9912909].

Opinion Leaders and Twitter: Metric Proposal and Psycholinguistic Analysis

Furini M.
;
2022

Abstract

Social media and personal health might be a dan-gerous combination: people are influenced by what they read online and don't pay attention to who wrote what they read. What happened during the COVID-19 pandemic? Who were the opinion leaders on social media? What were the conversations about? How did the health institutions communicate? To under-stand this, we focus on Twitter, and we analyze more than three million of Italian-written tweets posted from January 2020 to December 2021. We propose a method to identify opinion leaders and to analyze the content of the conversations. Results show that: (i) opinion leaders are linked to what they say and when they say it; (ii) politicians, newscast, and ordinary people accounts were able to become opinion leaders during the pandemic; (iii) conversations moved from a medical focus (at the beginning of the pandemic) to a social focus (in the last months of 2021); (iv) absence of health care institutions among opinion leaders. These results show that our approach might be useful for those who want to monitor the social scenario in terms of health (e.g., to identify as soon as possible accounts against or critical to medicine or to health authorities).
2022
no
Inglese
27th IEEE Symposium on Computers and Communications, ISCC 2022
Greece
2022
Proceedings - IEEE Symposium on Computers and Communications
2022-
1
5
978-1-6654-9792-3
Institute of Electrical and Electronics Engineers Inc.
345 E 47TH ST, NEW YORK, NY 10017 USA
Health-based conversations; opinion leaders; psycho-linguistics anal-ysis; social media sensing
Furini, M.; Flisi, E.
Atti di CONVEGNO::Relazione in Atti di Convegno
273
2
Opinion Leaders and Twitter: Metric Proposal and Psycholinguistic Analysis / Furini, M.; Flisi, E.. - 2022-:(2022), pp. 1-5. ( 27th IEEE Symposium on Computers and Communications, ISCC 2022 Greece 2022) [10.1109/ISCC55528.2022.9912909].
none
info:eu-repo/semantics/conferenceObject
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1316373
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