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Characterizing multi-domain false news and underlying user effects on Chinese Weibo

文献类型：期刊论文

作者Sheng, Qiang1,4; Cao, Juan1,4; Bernard, H. Russell5; Shu, Kai2; Li, Jintao4; Liu, Huan3
刊名INFORMATION PROCESSING & MANAGEMENT
出版日期2022-07-01
卷号59期号:4页码:18
关键词Multi-domain False news User effects Social media Weibo
ISSN号0306-4573
DOI10.1016/j.ipm.2022.102959
英文摘要False news that spreads on social media has proliferated over the past years and has led to multi-aspect threats in the real world. While there are studies of false news on specific domains (like politics or health care), little work is found comparing false news across domains. In this article, we investigate false news across nine domains on Weibo, the largest Twitter-like social media platform in China, from 2009 to 2019. The newly collected data comprise 44,728 posts in the nine domains, published by 40,215 users, and reposted over 3.4 million times. Based on the distributions and spreads of the multi-domain dataset, we observe that false news in domains that are close to daily life like health and medicine generated more posts but diffused less effectively than those in other domains like politics, and that political false news had the most effective capacity for diffusion. The widely diffused false news posts on Weibo were associated strongly with certain types of users -by gender, age, etc. Further, these posts provoked strong emotions in the reposts and diffused further with the active engagement of false-news starters. Our findings have the potential to help design false news detection systems in suspicious news discovery, veracity prediction, and display and explanation. The comparison of the findings on Weibo with those of existing work demonstrates nuanced patterns, suggesting the need for more research on data from diverse platforms, countries, or languages to tackle the global issue of false news. The code and new anonymized dataset are available at https://github.com/ICTMCG/Characterizing-Weibo-Multi-Domain-False-News.
资助项目National Key Research and Development Program of China[2021AAA0140203] ; Zhejiang Provincial Key Research and Development Program of China[2021C01164]
WOS研究方向Computer Science ; Information Science & Library Science
语种英语
WOS记录号WOS:000832363100007
出版者ELSEVIER SCI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/19478]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Cao, Juan
作者单位1.Univ Chinese Acad Sci, Beijing, Peoples R China
2.IIT, Dept Comp Sci, Chicago, IL 60616 USA
3.Arizona State Univ, Comp Sci & Engn, Tempe, AZ USA
4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
5.Arizona State Univ, Inst Social Sci Res, Tempe, AZ USA
推荐引用方式
GB/T 7714		 Sheng, Qiang,Cao, Juan,Bernard, H. Russell,et al. Characterizing multi-domain false news and underlying user effects on Chinese Weibo[J]. INFORMATION PROCESSING & MANAGEMENT,2022,59(4):18.
APA Sheng, Qiang,Cao, Juan,Bernard, H. Russell,Shu, Kai,Li, Jintao,&Liu, Huan.(2022).Characterizing multi-domain false news and underlying user effects on Chinese Weibo.INFORMATION PROCESSING & MANAGEMENT,59(4),18.
MLA Sheng, Qiang,et al."Characterizing multi-domain false news and underlying user effects on Chinese Weibo".INFORMATION PROCESSING & MANAGEMENT 59.4(2022):18.

入库方式： OAI收割

来源：计算技术研究所

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