Shuai Zhang1, Wenjing Pian2, Feicheng Ma1, Zhenni Ni1, Yunmei Liu1. 1. School of Information Management, Wuhan University, No 299 Bayi Road, Wuchang District, Wuhan, CN. 2. School of Economics and Management, Fuzhou University, Fuzhou, CN.
Abstract
BACKGROUND: The COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people's health and governance systems. OBJECTIVE: This study investigates and analyses the posts related to the COVID-19 misinformation on major Chinese social media to characterize the COVID-19 infodemic. METHODS: We collected posts about the COVID-19 misinformation on major Chinese social media from 20th Jan to 28th May 2020, using the Python toolkit. We used content analysis to identify the quantity and source of posts prevalent around the COVID-19 infodemic and used topic modeling to cluster the theme of the COVID-19 infodemic. Then, we explore the quantity, sources, and theme characteristics of the COVID-19 infodemic over time. RESULTS: The results show that: (1) the daily number of posts related to the COVID-19 infodemic on Chinese social media is positively correlated with the daily number of the newly confirmed cases (r=0.672, P＜0.01) and newly suspected cases (r=0.497, P＜0.01). (2) The COVID-19 infodemic showed a characteristic of gradual progress, which can be divided into five stages: incubation period, outbreak period, stalemate period, control period, and recovery period. (3) The sources of the COVID-19 infodemic can be divided into five types, namely chat platforms (40.1%), video-sharing platforms (23.4%), news-sharing platforms (22.1%), healthcare communities (8.7%), and Q&A communities (5.7%), which were slightly different at each stage. (4) The themes of COVID-19 infodemic were clustered into eight categories, namely "conspiracy theories" (23.6%), "government response" (19.8%), "prevention action" (15.0%), "new cases" (13.3%), "transmission routes" (8.9%), "origin and nomenclature" (8.3%), "vaccines and medicines" (5.6%), and "symptoms and detection" (5.5%), which were prominently diverse in different stages. Additionally, the COVID-19 infodemic showed a characteristic of repeated fluctuations. CONCLUSIONS: Our study found that the COVID-19 infodemic on Chinese social media was characterized by gradual progress, videoizing, and repeated fluctuations. We were able to show that the COVID-19 infodemic is paralleled to the propagation of the COVID-19 epidemic. We have tracked the COVID-19 infodemic across Chinese social media, providing critical new insights into the characteristics of infodemic and pointing out opportunities for preventing and controlling the COVID-19 infodemic.
BACKGROUND: The COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people's health and governance systems. OBJECTIVE: This study investigates and analyses the posts related to the COVID-19 misinformation on major Chinese social media to characterize the COVID-19 infodemic. METHODS: We collected posts about the COVID-19 misinformation on major Chinese social media from 20th Jan to 28th May 2020, using the Python toolkit. We used content analysis to identify the quantity and source of posts prevalent around the COVID-19 infodemic and used topic modeling to cluster the theme of the COVID-19 infodemic. Then, we explore the quantity, sources, and theme characteristics of the COVID-19 infodemic over time. RESULTS: The results show that: (1) the daily number of posts related to the COVID-19 infodemic on Chinese social media is positively correlated with the daily number of the newly confirmed cases (r=0.672, P＜0.01) and newly suspected cases (r=0.497, P＜0.01). (2) The COVID-19 infodemic showed a characteristic of gradual progress, which can be divided into five stages: incubation period, outbreak period, stalemate period, control period, and recovery period. (3) The sources of the COVID-19 infodemic can be divided into five types, namely chat platforms (40.1%), video-sharing platforms (23.4%), news-sharing platforms (22.1%), healthcare communities (8.7%), and Q&A communities (5.7%), which were slightly different at each stage. (4) The themes of COVID-19 infodemic were clustered into eight categories, namely "conspiracy theories" (23.6%), "government response" (19.8%), "prevention action" (15.0%), "new cases" (13.3%), "transmission routes" (8.9%), "origin and nomenclature" (8.3%), "vaccines and medicines" (5.6%), and "symptoms and detection" (5.5%), which were prominently diverse in different stages. Additionally, the COVID-19 infodemic showed a characteristic of repeated fluctuations. CONCLUSIONS: Our study found that the COVID-19 infodemic on Chinese social media was characterized by gradual progress, videoizing, and repeated fluctuations. We were able to show that the COVID-19 infodemic is paralleled to the propagation of the COVID-19 epidemic. We have tracked the COVID-19 infodemic across Chinese social media, providing critical new insights into the characteristics of infodemic and pointing out opportunities for preventing and controlling the COVID-19 infodemic.
Authors: Matheus Lotto; Olivia Santana Jorge; Tamires Sá Menezes; Ana Maria Ramalho; Thais Marchini Oliveira; Fernando Bevilacqua; Thiago Cruvinel Journal: JMIR Res Protoc Date: 2022-06-16