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Readability of Posts and User Engagement in Online Communities of Government Executive Bodies

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Social Computing and Social Media: Experience Design and Social Network Analysis (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12774))

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Abstract

The article deals with the question of the link between readability and engagement rates on social media. On one hand, easy-to-read texts can be useful to attract and involve broader audience, but on the other hand, texts which draw attention and spark discussions often tend to be complex, controversial, even sophisticated, and consequentially less readable. Our database consisted of 115245 posts retrieved from social networking site VKontakte, the most popular SNS in Russia. The sample included all publicly available posts in online communities of 47 Russian state bodies: ministries, federal services and federal agencies published from 01.01.2017 to 16.09.2020. For each post, engagement rate (ER) and 79 other metrics of the texts were calculated. Gradient Boosted Decision Trees were used to build the regression model which took into account all the features including 10 different readability metrics and other measures, such as topics, linguistic characteristics, sentiment and so on. As a result, the most significant factors were the variables determining the presence of certain topics. All readability scores were weak predictors of engagement rate. And furthermore, our data provided no evidence that topics can help to increase ER, but only the topics causing lowering of ER. Using correlation analysis, we showed that in the case of communication strategies in online communities in social network VKontakte, the readability of posts is not directly related to engagement rates.

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Acknowledgement

The reported study was funded by RFBR and EISR according to the research project № 20-011-31318.

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Authors and Affiliations

  1. Center for Sociological and Internet Research, Saint Petersburg State University, Saint Petersburg, Russia

    Konstantin Platonov

  2. Laboratory for Research of Social-Economic and Political Processes of Modern Society, Saint Petersburg State University, Saint Petersburg, Russia

    Kirill Svetlov

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  1. Konstantin Platonov
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  1. Department of Computer Science, Towson University, Towson, MD, USA

    Gabriele Meiselwitz

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Platonov, K., Svetlov, K. (2021). Readability of Posts and User Engagement in Online Communities of Government Executive Bodies. In: Meiselwitz, G. (eds) Social Computing and Social Media: Experience Design and Social Network Analysis . HCII 2021. Lecture Notes in Computer Science(), vol 12774. Springer, Cham. https://doi.org/10.1007/978-3-030-77626-8_22

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  • DOI: https://doi.org/10.1007/978-3-030-77626-8_22

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