COVID-19; Information diffusion; subjective well-being; Twitter; Bridging performance; Social media; Well being
Résumé :
[en] The outbreak of the COVID-19 pandemic triggered the perils of misinformation over social media. By amplifying the spreading speed and popularity of trustworthy information, influential social media users have been helping overcome the negative impacts of such flooding misinformation. In this article, we use the COVID-19 pandemic as a representative global health crisisand examine the impact of the COVID-19 pandemic on these influential users’ subjective well-being (SWB), one of the most important indicators of mental health. We leverage X (formerly known as Twitter) as a representative social media platform and conduct the analysis with our collection of 37,281,824 tweets spanning almost two years. To identify influential X users, we propose a new measurement called user bridging performance (UBM) to evaluate the speed and wideness gain of information transmission due to their sharing. With our tweet collection, we manage to reveal the more significant mental sufferings of influential users during the COVID-19 pandemic. According to this observation, through comprehensive hierarchical multiple regression analysis, we are the first to discover the strong relationship between individual social users’ subjective well-being and their bridging performance. We proceed to extend bridging performance from individuals to user subgroups. The new measurement allows us to conduct a subgroup analysis according to users’ multilingualism and confirm the bridging role of multilingual users in the COVID-19 information propagation. We also find that multilingual users not only suffer from a much lower SWB in the pandemic, but also experienced a more significant SWB drop.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
CHEN, Ninghan ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Computer Science > Team Jun PANG
CHEN, Xihui ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Computer Science > Team Sjouke MAUW
ZHONG, Zhiqiang ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Computer Science > Team Jun PANG ; Faculty of Natural Sciences, Aarhus University, Aarhus, Denmark
PANG, Jun ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Bridging Performance of X (formerly known as Twitter) Users: A Predictor of Subjective Well-Being During the Pandemic
FNR16281848 - Give Control Back To Users: Personalised Privacy-preserving Data Aggregation From Heterogeneous Social Graphs, 2021 (01/04/2022-31/03/2025) - Sjouke Mauw FNR12252781 - Data-driven Computational Modelling And Applications, 2017 (01/09/2018-28/02/2025) - Andreas Zilian FNR10621687 - Security And Privacy For System Protection, 2015 (01/01/2017-30/06/2023) - Sjouke Mauw
Organisme subsidiant :
Luxembourg National Research Fund
Subventionnement (détails) :
This research was funded in whole, or in part, by the Luxembourg National Research Fund (FNR), grant reference C21/IS/16281848 (HETERS), COVID-19/2020-1/14700602 (PandemicGR), PRIDE17/12252781 (DRIVEN) and PRIDE15/ 10621687 (SPsquaredand). For the purpose of open access, the author has applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission.
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