This study analyzed Weibo posts that contain stigma towards Wuhan people during the COVID-19 epidemic to target-specific stigmatizing attitudes and analyzed their changes in different periods of the epidemic. Results indicated that there are different attitudes associated with the stigma towards Wuhan people in Weibo and they changed in different periods of the epidemic.
Among posts related to the COVID-19, stigmatizing posts only account for 2.46%, which is relatively low compared with stigmatizing tweets towards the Chinese in America between March 9 and March 25 [8]. Nevertheless, according to Fig. 4, the percentage of stigmatizing posts reached a peak point above 16% on Jan 18, 2020 and percentages of ‘Stupid’ and ‘Irresponsible’ posts rose earlier than ‘Infectious’. These results indicate that stigma towards Wuhan people on Weibo was relatively mild in severity from the whole period, but it was rather severe at pre-GI with ‘Irresponsible’ and ‘Stupid’ attitudes.
While the daily percentages of posts depict subtle changes of stigma, the results from repeated measures ANOVA give a statistical comparison of stigma in different periods. The main effects of periods on stigmatizing posts, ‘Infectious’ posts, and ‘Stupid’ posts are significant, whereas ‘Irresponsible’ posts are not. This suggests that government interventions can reduce stigma with ‘Infectious’ and ‘Stupid’ attitudes, but they have no significant influence on stigma with ‘Irresponsible’ attitude.
In the post-hoc analysis, we focus on the difference from pre-GI to post-GI, and from post-GI to eff-GI. Although not significantly, the stigmatizing posts, ‘Stupid’ posts, and ‘Irresponsible’ posts reduced from pre-GI to post-GI according to Table 3. In the meantime, however, ‘Infectious’ posts increased significantly. From post-GI to eff-GI, stigmatizing posts, ‘Stupid’ posts, and ‘Infectious’ posts reduced significantly. These results suggest that the government interventions (GI) have a negative short-term effect on ‘Infectious’ stigma, but a positive long-term effect on ‘Stupid’ stigma, ‘Infectious’ stigma, and general stigma.
‘Wuhan people are infectious’ is the most common attitude associated with stigma compared with the two other types. This type of stigma is very common in other diseases [33–35]. Previous research found that Ebola-related stigma subsided as the Ebola virus disease relieved in Liberia and increased every time the disease re-emerged. In this study, we found the same consistency between ‘Infectious’ stigma and severity of the disease. From pre-GI to post-GI, the number of confirmed COVID-19 cases continued increasing, and ‘Infectious’ posts increased significantly. From post-GI to eff-GI, as the epidemic under control, it decreased significantly. More importantly, government interventions such as city lockdown and home quarantine orders may reinforce public’s biased perceptions about the stigmatized group without realizing it because they are following their supervisors[12]. This also explained why ‘Infectious’ stigma increased at post-GI.
The reason for the occurrence of ‘Stupid’ stigma may be that, people at pre-GI are facing a novel disease, thus speculating that the outbreak may be related to the consumption of wild animals based on the experience of SARS in the past. This form of stigmatizing attitude associates local culture with the disease and obfuscates the scientific causes of epidemics, which was also common during the SARS and H1N1 epidemic [20, 33]. At post-GI, ‘Stupid’ stigma did not decrease significantly, indicating the popularization to the public of scientific causes of the disease was not enough at this period. Fortunately, ‘Stupid’ labels decreased significantly at eff-GI.
Unlike other attitudes, the ‘Irresponsible’ stigma didn’t decrease significantly at eff-GI. According to the attribution theory [7], when people gain a strong sense of control over infectious diseases, assuming responsibility for the occurrence of a disease is easy to be attributed to the individuals. At eff-GI, effective control of the epidemic made the public raise their expectations for individuals to avoid spreading the disease. As a result, although the number of confirmed cases decreased, people are more likely to blame the affected individuals for these cases. Thus, stigmatizing posts continued labeling Wuhan people irresponsible for escaping isolation orders.
Researches on other diseases found gender differences exist in stigma expressions [14, 36, 37]. In this study, however, no gender difference was found in general stigma or any attitudes of stigma. More researches are needed to identify gender-specific demographic and cognitive factors associated with stigma related to COVID-19.
With previous studies proved stigma exists long after SARS [38], and with the potential re-emergence of COVID-19 any time in the future, COVID-19 related stigma could be a long-lasting problem. Our findings can provide certain information for stigma mitigation. First, government interventions for disease control cannot mitigate stigma immediately. Second, stigma mitigation strategies should target specific attitudes in different periods of the epidemic. At pre-GI, a blank in scientific understanding existed for a relatively long period. During this stage, stigma with ‘Stupid’ attitude is prevalent due to the lack of scientific explanations of the disease. Target-specific strategies should be correcting the biased explanations about the origins of the disease. At post-GI, policymakers should consider the effects of isolation measures on stigma to avoid reinforcing stigma with ‘Infectious’ attitude. At eff-GI, people tended to attribute the spread of the epidemic to individuals and label the individuals with ‘Irresponsible’ tags. This notion suggests that officials should explain the objective reasons for the spread of the epidemic to the public in a timely manner.
This study has certain limitations. Firstly, attitudes towards Wuhan people online may differ from attitudes displayed offline. Secondly, social media users form only a sample of the Chinese population, which may not be representative of all people in China. Thirdly, users’ demographic information is obtained from profiles, which cannot be verified. Finally, changes in different periods can only be compared over time, thus the direct causality between government interventions and stigma cannot be guaranteed.