Evaluating Rumor Debunking Effectiveness During the COVID-19 Pandemic Crisis: Utilizing User Stance in Comments on Sina Weibo

Abstract

Background: The spread of rumors related to COVID-19 on social media has posed substantial challenges to public health governance, and thus exposing rumors and curbing their spread quickly and effectively has become an urgent task. This study aimed to assist in formulating effective strategies to debunk rumors and curb their spread on social media.Methods: A total of 2,053 original postings and 100,348 comments that replied to the postings of five false rumors related to COVID-19 (dated from January 20, 2020, to June 28, 2020) belonging to three categories, authoritative, social, and political, on Sina Weibo in China were randomly selected. To study the effectiveness of different debunking methods, a new annotation scheme was proposed that divides debunking methods into six categories: denial, further fact-checking, refutation, person response, organization response, and combination methods. Text classifiers using deep learning methods were built to automatically identify four user stances in comments that replied to debunking postings: supporting, denying, querying, and commenting stances. Then, based on stance responses, a debunking effectiveness index (DEI) was developed to measure the effectiveness of different debunking methods.Results: The refutation method with cited evidence has the best debunking effect, whether used alone or in combination with other debunking methods. For the social category of Car rumor and political category of Russia rumor, using the refutation method alone can achieve the optimal debunking effect. For authoritative rumors, a combination method has the optimal debunking effect, but the most effective combination method requires avoiding the use of a combination of a debunking method where the person or organization defamed by the authoritative rumor responds personally and the refutation method.Conclusion: The findings provide relevant insights into ways to debunk rumors effectively, support crisis management of false information, and take necessary actions in response to rumors amid public health emergencies.

Improving the Communication and Credibility of Government Media in Response to Public Health Emergencies: Analysis of Tweets From the WeChat Official Accounts of 10 Chinese Health Commissioners

“…In the early phases of the pandemic, the government used Weibo post data to determine the outbreak's stage of development, allowing them to take proper steps (23). According to an analysis of Chinese Weibo user postings, it can be found that the method for debunking rumors varies based on the type of rumor (24). In Macau, different levels of information disclosure to varying epidemic stages through the government's Facebook have effectively addressed the public health crisis (25).…”

Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic

“…Liu et al introduced the first real-time rumor debunking algorithm for social media [ 41 ]. Wang et al divided rumor debunking methods into six categories (i.e., denial, further fact-checking, refutation, person response, organization response, and combination methods), of which the refutation method has the best debunking effect [ 42 ]. Other researchers tried to find out influencing factors related to rumors.…”

Establishing the typology and the underlying structure of rumor-combating behaviors: a multidimensional scaling approach

“…These rumor-combating behaviors may occur in different stages of rumor spreading (Chen et al. , 2018; Wang and Zhuang, 2018) and have different governance effects and occurrence frequencies (Wang and Zhuang, 2018; Wang et al. , 2021).…”

“…Usually, official verification and refutation reports appear after false rumors have been widely circulated, resulting in much misinformation not being corrected in time (Tang et al, 2021). Even when debunking messages are sometimes released, these facts often reach a narrow audience and cannot be effectively disseminated (Wang et al, 2021). Moreover, only the most widespread rumors typically attract attention from authorities and mainstream media (Zhao et al, 2015).…”

“…, 2021). Even when debunking messages are sometimes released, these facts often reach a narrow audience and cannot be effectively disseminated (Wang et al. , 2021).…”