Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic

Zixuan Weng and Aijun Lin ()
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Zixuan Weng: School of Journalism and Communication, Jinan University, Guangzhou 510632, China
Aijun Lin: School of Journalism and Communication, Jinan University, Guangzhou 510632, China

IJERPH, 2022, vol. 19, issue 24, 1-17

Abstract: Social media is not only an essential platform for the dissemination of public health-related information, but also an important channel for people to communicate during the COVID-19 pandemic. However, social bots can interfere with the social media topics that humans follow. We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.

Keywords: social bot; public opinion manipulation; social network; COVID-19; Latent Dirichlet Allocation; natural language processing; human-machine communication; Botometer; Wuhan lab; China (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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