Individual users' participation on political Facebook pages

Authors

  • Yannick Winkler University of Hohenheim
  • Marko Bachl University of Hohenheim
  • Michael Scharkow Johannes Gutenberg University Mainz

DOI:

https://doi.org/10.51685/jqd.2022.019

Keywords:

social media, Facebook, individual user behavior, political participation, digital traces, computational methods

Abstract

Social media platforms such as Facebook enable citizens to participate in politics by engaging with content from parties and politicians. Most research has described these activites by means of survey self-reports, smaller sample studies which combined surveys and digital trace data, or larger-scale aggregate digital trace data. The current literature lacks a large-scale descriptive account of individual users' interactions with political content. We analyze a large-scale collection of individual-level Facebook user data from the German federal election year 2017. The data contain millions of interactions by over 2.5 million unique users on 320 Facebook pages of major parties in Germany. They include almost all possible ways to publicly interact with content on these pages and as such cannot be collected today due to newer access restrictions. A large share of users participated only once, especially on the top politicians' pages, or interacted only with a single page. However, we also found a sizeable group of users who were active on many different pages even across party boundaries, and that these users were responsible for a majority of comments and reactions on almost all pages. In addition, there were substantial differences in user participation on the main national party pages and the ones of top politicians on the one hand, and the less prominent pages on the other hand. Our large-scale quantitative description provides context for previous and future smaller-scale in-depth analyses.

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Published

2022-08-09

How to Cite

Winkler, Y., Bachl, M., & Scharkow, M. (2022). Individual users’ participation on political Facebook pages. Journal of Quantitative Description: Digital Media , 2. https://doi.org/10.51685/jqd.2022.019

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Articles