Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic

Background Social media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic. Methods Content analysis was conducted to scrutinize the official (national and provincial) public health agencies’ Weibo posts (n = 4396) to identify features of information sources and message features (structure, style content). The Zero-Inflated Negative Binomial (ZINB) model was adopted to analyze the association between these features and the frequency of the retweeted messages. Results Results indicated that features of source and health information, such as structure, style, and content, were correlated to retweeting. The results of IRR further suggested that compared to provincial accounts, messages from national health authorities’ accounts gained more retweeting. Regarding the information features, messages with hashtags#, picture, video have been retweeted more often than messages without any of these features respectively, while messages with hyperlinks received fewer retweets than messages without hyperlinks. In terms of the information structure, messages with the sentiment (!) have been retweeted more frequently than messages without sentiment. Concerning content, messages containing severity, reassurance, efficacy, and action frame have been retweeted with higher frequency, while messages with uncertainty frames have been retweeted less often. Conclusions Health organizations and medical professionals should pay close attention to the features of health information sources, structures, style, and content to satisfy the public’s information needs and preferences to promote the public's health engagement. Designing suitable information systems and promoting health communication strategies during different pandemic stages may improve public awareness of the COVID-19, alleviate negative emotions, and promote preventive measures to curb the spread of the virus.

Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic.

BACKGROUND: Social media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic. METHODS: Content analysis was conducted to scrutinize the official (national and provincial) public health agencies' Weibo posts (n = 4396) to identify features of information sources and message features (structure, style content). The Zero-Inflated Negative Binomial (ZINB) model was adopted to analyze the association between these features and the frequency of the retweeted messages. RESULTS: Results indicated that features of source and health information, such as structure, style, and content, were correlated to retweeting. The results of IRR further suggested that compared to provincial accounts, messages from national health authorities' accounts gained more retweeting. Regarding the information features, messages with hashtags#, picture, video have been retweeted more often than messages without any of these features respectively, while messages with hyperlinks received fewer retweets than messages without hyperlinks. In terms of the information structure, messages with the sentiment (!) have been retweeted more frequently than messages without sentiment. Concerning content, messages containing severity, reassurance, efficacy, and action frame have been retweeted with higher frequency, while messages with uncertainty frames have been retweeted less often. CONCLUSIONS: Health organizations and medical professionals should pay close attention to the features of health information sources, structures, style, and content to satisfy the public's information needs and preferences to promote the public's health engagement. Designing suitable information systems and promoting health communication strategies during different pandemic stages may improve public awareness of the COVID-19, alleviate negative emotions, and promote preventive measures to curb the spread of the virus.

Which Information Frame is Best for Reporting News on the COVID-19 Pandemic? An Online Questionnaire Study in China.

INTRODUCTION: The COVID-19 pandemic has received broad public attention and has been subject to social media discussion since the beginning of 2020. Previous research has demonstrated that framing could influence perception and behaviors of audience members in the mass media. The question addressed in this paper concerns which information frame is best for reporting negative news (eg, deaths) and positive news (eg, recoveries or cures) related to the outbreak of COVID-19. METHODS: During the Spring Festival holidays of 2020 in China, we investigated a sample of 8170 participants' risk perceptions and emotional responses to the pandemic, and their willingness to forward updates when the information is presented in different frames by using a 2 (domain: living [good news] vs dying [bad news]) × 2 (count: absolute vs relative) × 2 (population base: excluding population base vs including population base) × 2 (content: text-only vs text-plus-graphic) mixed factorial design, with the first factor being a within-subjects factor and the last three being between-subjects factors. RESULTS: Results indicated that (1) participants were more willing to forward good news (eg, cures) than bad news (eg, deaths); (2) when reporting bad news, the inclusion of the "population base" was effective in minimizing negative emotions; (3) when reporting good news, excluding the "population base" was more effective than including it in order to maximize positive emotions; (4) a text-plus-graphic frame worked better than a text-only frame in lowering the level of risk perception and negative emotions. DISCUSSION: This study is relevant to how individuals and organizations communicate information about this viral pandemic and the probable impact of this news on the general public.