Debate on online social networks at the time of COVID-19: An Italian case study

Q1 Social Sciences Online Social Networks and Media Pub Date : 2021-05-01 DOI:10.1016/j.osnem.2021.100136
Martino Trevisan, Luca Vassio, Danilo Giordano
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引用次数: 20

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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COVID-19时期关于在线社交网络的争论:以意大利为例
新冠肺炎大流行不仅对医疗保健产生了严重影响,而且正在改变人们的生活习惯和我们所处的社会。意大利等国实施了持续数月的全面封锁,大多数人口被迫留在家中。在此期间,在线社交网络比以往任何时候都更代表了社交生活的另一种解决方案,允许用户相互互动和辩论。因此,了解疫情给社交网络的使用带来的变化至关重要。在本文中,我们分析了2020年前六个月意大利在Instagram和Facebook社交网络中围绕热门网红的互动模式是如何变化的。我们为这组公众人物收集了一个庞大的数据集,包括这几个月来14万多条帖子的5400多万条评论。我们分析和比较这些网红帖子的参与度,并提供汇总用户活动的定量数据。我们进一步展示了封锁前和期间使用模式的变化,显示出活动的增长以及每日和每周的巨大变化。我们还通过评论的心理语言学特性分析了用户情绪,结果证明了与疫情相关的话题的快速繁荣和消失。为了支持进一步的分析,我们发布了匿名数据集。
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来源期刊
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
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