Debate on Online Social Networks at the Time of COVID-19: An Italian Case Study

• URL: http://arxiv.org/abs/2106.01013v1
• Date: Wed, 2 Jun 2021 08:25:19 GMT
• Title: Debate on Online Social Networks at the Time of COVID-19: An Italian Case Study
• Authors: Martino Trevisan, Luca Vassio, Danilo Giordano
• Abstract summary: We analyze how the interaction patterns around popular influencers in Italy changed during the first six months of 2020. We collected a large dataset for this group of public figures, including more than 54 million comments on over 140 thousand posts. We also analyze the user sentiment through the psycholinguistic properties of comments, and the results testified the rapid boom and disappearance of topics related to the pandemic.
• Score: 4.176752121302988
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The COVID-19 pandemic is not only having a heavy impact on healthcare but also changing people's habits and the society we live in. Countries such as Italy have enforced a total lockdown lasting several months, with most of the population forced to remain at home. During this time, online social networks, more than ever, have represented an alternative solution for social life, allowing users to interact and debate with each other. Hence, it is of paramount importance to understand the changing use of social networks brought about by the pandemic. In this paper, we analyze how the interaction patterns around popular influencers in Italy changed during the first six months of 2020, within Instagram and Facebook social networks. We collected a large dataset for this group of public figures, including more than 54 million comments on over 140 thousand posts for these months. We analyze and compare engagement on the posts of these influencers and provide quantitative figures for aggregated user activity. We further show the changes in the patterns of usage before and during the lockdown, which demonstrated a growth of activity and sizable daily and weekly variations. We also analyze the user sentiment through the psycholinguistic properties of comments, and the results testified the rapid boom and disappearance of topics related to the pandemic. To support further analyses, we release the anonymized dataset.

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