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. (Intervento presentato al convegno 27th IEEE Symposium on Computers and Communications, ISCC 2022 tenutosi a Greece nel 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).Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris