Primacy effect of emotions in social stories: User engagement behaviors with breast cancer narratives on Facebook

Zhao, Xinyan; Wang, Xiaohui; Ma, Zexin; Ma, Rong

doi:10.1016/j.chb.2022.107405

Cited by 11 publications

(1 citation statement)

References 48 publications

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“…During the outbreak, a combination of guidance/education/advice/appeal and negative emotions was most likely to promote citizen engagement, followed by positive emotional appeal. In agreement with reports on article content related to the pandemic [ 17 ], cancer [ 42 ], and so on, negative emotions lead to increase engagement. This finding might be due to articles with negative emotions article contents spreading faster, especially when facing to unexpected events [ 43 , 44 ].…”

Section: Discussionsupporting

confidence: 84%

Effects of Chinese provincial CDCs WeChat official account article features on user engagement during the COVID-19 pandemic

Yin¹,

Chen²,

Pan³

et al. 2023

J Glob Health

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Background WeChat has become a potent medium for disseminating public health information, especially during the coronavirus disease 2019 (COVID-19) pandemic. WeChat is important for public health organizations when considering users’ information needs and preferences to further explore factors that affect user engagement. Methods We collected data from WeChat official accounts (WOAs) of the Chinese provincial Center for Disease Control and Prevention (CDC) to identify factors affecting and predicting the behavior of user engagement as measured by the level of reading and re-sharing during different phases of the COVID-19 pandemic between January 1, 2019, and December 31, 2020. We used multiple logistic regression analyses to identify features of articles with higher reading and re-sharing levels from 31 Chinese provincial CDCs. We developed a nomogram to predict the effect on user engagement. Results We collected a total of 26 302 articles. Release position, title type, article content, article type, communication skills, marketing elements, article length, and video length were key determinants of user engagement. Although the feature patterns also varied between different pandemic stages, the article content, release position, and article type were still the most prominent features driving user engagement. Regarding article content, the COVID-19 pandemic report and guidance for public protection were more likely to obtain high-level reading (normalization: odds ratio (OR) = 12.340, 95% confidence interval (CI) = 9.357-16.274) and re-sharing (normalization: OR = 7.254, 95% CI = 5.554-9.473) than other contents throughout the pandemic. When we compared release position with secondary push, users who used main push were more likely to exhibit high-level reading and re-sharing during any period, especially during normalization (OR = 6.169, 95% CI = 5.554-6.851; OR = 4.230, 95% CI = 3.833-4.669). For article type, a combination of text, links and pictures was associated with a higher rate of reading (normalization: OR = 4.262, 95% CI = 3.509-5.176) and re-sharing level (normalization: OR = 4.480, 95% CI = 3.635-5.522) compared to text only. Simultaneously, the prediction model showed good discriminatory power and calibration. Conclusions Discrepancies exist in article features between different pandemic stages. Public health agencies should make full use of official WOAs and consider the information needs and preferences of users in order to better carry out health education and health communication with the public when public health events occur.

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