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Facebook Explore Feed: Perception and Consequences of the Experiment

Author

Listed:
  • Martin Kuchta

    (University of Economics in Bratislava)

  • Linda Vaskova

    (University of Economics in Bratislava)

  • Andrej Miklosik

    (University of Economics in Bratislava)

Abstract

Facebook is the most used social network in the world. It dedicates a lot of energy and resources to developing and fine-tuning its algorithms, thus enabling it to serve accurate content to eligible users and to fulfill the expectations of every entity that utilizes the platform. These algorithms need to evolve in time to adapt to the changing preferences of Facebook and its users. The evolution of the adjustments in the algorithms is a demanding process, mainly (but not only) because of the enormous number of its users. Changes need to be tested first, and this approach has been applied to the Explore Feed, which divides the Facebook News Feed into two sections. One section is for friends’ content only and the second is dedicated solely to the content of media and organizations. Slovakia represents one of the six countries where the test was executed. The aim of this article is to identify and summarize perceptions and feedback on the Explore Feed and to determine the consequences of similar tests for global firms. This paper presents the results of a survey devoted to an examination of the perceptions of the Facebook Explore Feed. Survey questions, collected answers, and an evaluation of the answers were conducted in cooperation (and consultation) with an independent local media publishing company and its website. This website was selected because of the demographic profile of its users who represent the target group who most frequently use the Facebook platform.

Suggested Citation

  • Martin Kuchta & Linda Vaskova & Andrej Miklosik, 2020. "Facebook Explore Feed: Perception and Consequences of the Experiment," The Review of Socionetwork Strategies, Springer, vol. 14(1), pages 93-107, April.
    • Handle: RePEc:spr:trosos:v:14:y:2020:i:1:d:10.1007_s12626-019-00050-4
    DOI: 10.1007/s12626-019-00050-4
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    References listed on IDEAS

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    1. Chunjing Xiao & Fan Zhou & Yue Wu, 2013. "Predicting audience gender in online content-sharing social networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(6), pages 1284-1297, June.
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    3. Long Song & Raymond Yiu Keung Lau & Ron Chi-Wai Kwok & Kristijan Mirkovski & Wenyu Dou, 2017. "Who are the spoilers in social media marketing? Incremental learning of latent semantics for social spam detection," Electronic Commerce Research, Springer, vol. 17(1), pages 51-81, March.
    4. Kaplan, Andreas M. & Haenlein, Michael, 2010. "Users of the world, unite! The challenges and opportunities of Social Media," Business Horizons, Elsevier, vol. 53(1), pages 59-68, January.
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