A COVID-19 Rumor Dataset

Frontiers in Psychology

article

Mingxi Cheng¹  Songli Wang²  Xiaofeng Yan³  Tianqi Yang⁴  Wenshuo Wang⁵  Zehao Huang¹  Xiongye Xiao¹  Shahin Nazarian¹  Paul Bogdan¹ 

[1] Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, United States;School of Computer Science, Fudan University;Department of Automation, Tsinghua University;UM-SJTU Joint Institute, Shanghai Jiao Tong University;Department of Automation, Beihang University

关键词: misinformation;    rumor;    COVID-19;    rumor classification;    sentiment analysis;    deep learning;    fake news detection;   

DOI  :  10.3389/fpsyg.2021.644801

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

The outbreak of the coronavirus disease (COVID-19) has caused widespread concerns among thepublic and has profoundly impacted social opinions since December 2019 (Nelson et al., 2020).Besides the disease itself, the pressure caused by the pandemic and the fear of disease spreadinghave become a psychological burden (Abdoli, 2020). Authors in (Luo et al., 2020) showed thatpatients with pre-existing conditions and COVID-19 infection are experiencing psychologicaldistress, anxiety, and depression. The ongoing pandemic has also aroused heated discussion onthe Internet (Cinelli et al., 2020). In response to the infodemic, scientists rise and fight againstrumors, conspiracy, misinformation, fake news, and disinformation (Gallotti et al., 2020; Jolleyand Paterson, 2020; Butcher, 2021; Cheng et al., 2021b). In this, all sorts of information aredisseminated in the form of news reports, tweets, etc. (Kouzy et al., 2020). Topics of publicdiscussion vary over time as the virus spreads rapidly, while real and fake information is mixed,leading to increasing confusion in some communities. Rumors are defined as statements or reportscurrently without known veracity concerning their truthfulness, (Friggeri et al., 2014) which spreadmisinformation/disinformation (deliberately misleading information) and cause panic, hatred, anddiscrimination (Depoux et al., 2020). Along with the rapid dissemination of misinformation,researchers discover a massive growth in fact-checks about COVID-19, e.g., the number of Englishlanguage fact-checks increased more than 900% from January to March 2020 (Brennen et al., 2020).Fact-checking websites such as the FactCheck.org (Brooks, 2020) and Poynter.org (Neil Brown,2020) are the primary sources of current COVID-19 misinformation/rumor data.

【 授权许可】

CC BY