Bridging Performance of Twitter Users: A Predictor of Subjective Well-Being during the Pandemic

IF 2.6 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Transactions on the Web Pub Date : 2023-11-30 DOI:10.1145/3635033
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
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Abstract

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 paper, we use the COVID-19 pandemic as a representative global health crisis and and 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 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 Twitter 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.

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Twitter用户的桥接性能:大流行期间主观幸福感的预测因子
COVID-19大流行的爆发引发了社交媒体上错误信息的危险。通过放大可信信息的传播速度和受欢迎程度,有影响力的社交媒体用户一直在帮助克服这种泛滥的错误信息的负面影响。在本文中,我们将COVID-19大流行作为具有代表性的全球健康危机,并研究了COVID-19大流行对这些有影响力的用户主观幸福感(SWB)的影响,这是心理健康最重要的指标之一。我们利用Twitter作为一个具有代表性的社交媒体平台,对近两年来收集的37,281,824条推文进行了分析。为了识别有影响力的Twitter用户,我们提出了一个名为用户桥接性能(UBM)的新度量来评估由于他们的共享而导致的信息传播的速度和广度增益。通过我们的推文收集,我们设法揭示了在COVID-19大流行期间有影响力的用户更重大的精神痛苦。根据这一观察,通过综合层次多元回归分析,我们首次发现了个人社交用户的主观幸福感与其桥接绩效之间存在很强的关系。我们继续将桥接性能从个人扩展到用户子组。新的衡量标准使我们能够根据用户的多语种进行分组分析,并确认多语种用户在COVID-19信息传播中的桥梁作用。我们还发现,在大流行期间,多语种用户不仅SWB低得多,而且SWB下降幅度更大。
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来源期刊
ACM Transactions on the Web
ACM Transactions on the Web 工程技术-计算机:软件工程
CiteScore
4.90
自引率
0.00%
发文量
26
审稿时长
7.5 months
期刊介绍: Transactions on the Web (TWEB) is a journal publishing refereed articles reporting the results of research on Web content, applications, use, and related enabling technologies. Topics in the scope of TWEB include but are not limited to the following: Browsers and Web Interfaces; Electronic Commerce; Electronic Publishing; Hypertext and Hypermedia; Semantic Web; Web Engineering; Web Services; and Service-Oriented Computing XML. In addition, papers addressing the intersection of the following broader technologies with the Web are also in scope: Accessibility; Business Services Education; Knowledge Management and Representation; Mobility and pervasive computing; Performance and scalability; Recommender systems; Searching, Indexing, Classification, Retrieval and Querying, Data Mining and Analysis; Security and Privacy; and User Interfaces. Papers discussing specific Web technologies, applications, content generation and management and use are within scope. Also, papers describing novel applications of the web as well as papers on the underlying technologies are welcome.
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