Abstract
While government microblogs show increasing significance as a bridge connecting the government and the people, its role has become more prominent during the covid-19 outbreak, when the government released all kinds of official information in a timely manner and obtained public participation and feedback. Two important aspects to measure online participation are likes and comments, and the content topic of posts is an important influencing factor in online engagement studies. However, except for a few case studies, few researches have been conducted to provide an objective insight into the content topics of government blogs based on amass data in the context of the epidemic, and subsequently studies the impact of content topics on engagements. This paper analyzes the overall release pattern of government microblogs during pandemic in China by extracting 9 topics through LDA model based-on datasets from Sina Weibo. With a 5W-framework, we empirically confirm the relationship between content topics and public engagement with negative binomial analysis beyond the limitations of previous studies focusing only on some local factors. The results show that in general government releases focus mainly on the topics of epidemic science and uplifting spirits. However, information about police and public interaction and important instructions receives more discussion and likes, while news about treatment progress and praise of uplifting spirits receive little attention. Contributions to the literature and practice are discussed.
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Acknowledgement
This research was supported by The Ministry of Education Humanities and Social Sciences Fund Project “Research on the mechanism and strategy of online medical precision service based on intelligent methods” (22YJA630018).
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Nie, A., Jiang, H., Xu, J., Fan, J. (2023). An Empirical Study on the Impact of Government Microblogs on Online Engagements During the Covid-19 Outbreak. In: Tu, Y., Chi, M. (eds) E-Business. Digital Empowerment for an Intelligent Future. WHICEB 2023. Lecture Notes in Business Information Processing, vol 480. Springer, Cham. https://doi.org/10.1007/978-3-031-32299-0_26
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