2021/10/22 by Yichi Qian, Qian, Yichi, Qiyi Shan +5
Computer Science · Social Sciences · #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #Misinformation and Its Impacts #Social Media and Politics #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2110.11919
openalex publication_date 2021/10/22 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
The emergence of social media has largely eased the way people receive\ninformation and participate in public discussions. However, in countries with\nstrict regulations on discussions in the public space, social media is no\nexception. To limit the degree of dissent or inhibit the spread of "harmful"\ninformation, a common approach is to impose information operations such as\ncensorship/suspension on social media. In this paper, we focus on a study of\ncensorship on Weibo, the counterpart of Twitter in China. Specifically, we 1)\ncreate a web-scraping pipeline and collect a large dataset solely focus on the\nreposts from Weibo; 2) discover the characteristics of users whose reposts\ncontain censored information, in terms of gender, device, and account type; and\n3) conduct a thematic analysis by extracting and analyzing topic information.\nNote that although the original posts are no longer visible, we can use\ncomments users wrote when reposting the original post to infer the topic of the\noriginal content. We find that such efforts can recover the discussions around\nsocial events that triggered massive discussions but were later muted. Further,\nwe show the variations of inferred topics across different user groups and time\nframes.\n