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Are citizens engaging with government social media Covid 19 pandemic information? Why media richness and dialogic loop features matter
The Electronic Journal of Information Systems in Developing Countries ; 2022.
Article in English | Web of Science | ID: covidwho-2121025
ABSTRACT
This study investigated the extent to which media richness, dialogic loop, and content type affect citizen engagement with local government social media information on the Covid-19 pandemic. Quantitative content analysis through scraping of Facebook posts by the local government was employed in this study. Effects of the determinant variables was tested using negative binomial regression. Results show that both media richness and dialogic loop have significant and positive effects on citizens' engagement. This means that the richer the media, and the more dialogic features present in a Facebook post, the higher the turnout of reactions, shares, and comments of such post. Content type, on the other hand, was found to have no significant effect, implying that the number of content categories a certain post belongs to does not influence engagement from citizens. The study focused only on the local government's pandemic information posted on Facebook. Local governments should continue utilizing social media in disseminating pandemic information, and in the process, consider maximum utilization of the social media features to generate more engagement from its citizens. This study is the first to determine the factors affecting citizen engagement with government social media during the Covid-19 pandemic in the Philippine context.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: The Electronic Journal of Information Systems in Developing Countries Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: The Electronic Journal of Information Systems in Developing Countries Year: 2022 Document Type: Article