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Social Bots' Involvement in the COVID-19 Vaccine Discussions on Twitter.
Zhang, Menghan; Qi, Xue; Chen, Ze; Liu, Jun.
  • Zhang M; Centre for Chinese Urbanization Studies of Soochow University & Collaborative Innovation Center for New Urbanization and Social Governance of Universities, Suzhou 215006, China.
  • Qi X; School of Communication, Soochow University, Suzhou 215123, China.
  • Chen Z; School of Communication, Soochow University, Suzhou 215123, China.
  • Liu J; School of Communication, Soochow University, Suzhou 215123, China.
Int J Environ Res Public Health ; 19(3)2022 01 31.
Article in English | MEDLINE | ID: covidwho-1667159
ABSTRACT
During the COVID-19 pandemic, social media served as an important channel for the public to obtain health information and disseminate opinions when offline communication was severely hindered. Yet the emergence of social bots influencing social media conversations about public health threats will require researchers and practitioners to develop new communication strategies considering their influence. So far, little is known as to what extent social bots have been involved in COVID-19 vaccine-related discussions and debates on social media. This work selected a period of nearly 9 months after the approval of the first COVID-19 vaccines to detect social bots and performed high-frequency word analysis for both social bot-generated and human-generated tweets, thus working out the extent to which social bots participated in the discussion on the COVID-19 vaccine on Twitter and their participation features. Then, a textual analysis was performed on the content of tweets. The findings revealed that 8.87% of the users were social bots, with 11% of tweets in the corpus. Besides, social bots remained active over three periods. High-frequency words in the discussions of social bots and human users on vaccine topics were similar within the three peaks of discourse.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Topics: Vaccines Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19031651

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Topics: Vaccines Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19031651