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Effects of Conspiracy Thinking Style, Framing and Political Interest on Accuracy of Fake News Recognition by Social Media Users: Evidence from Russia, Kazakhstan and Ukraine

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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

This study examines the effect of specific factors (including user features, such as propensity for conspiracy thinking, and news item features, such as news frame and news source) on the accuracy of social media users in fake news recognition. Being a part of a larger research on fake news perception, this study uses the data from an online experiment that asks social media users from three countries (Russia, Ukraine and Kazakhstan) to evaluate a set of news items constructed with specific conditions. Namely, the users receive true and fake news about the neighboring countries framed differently and ascribed to either domestic or foreign sources. We then assess users’ accuracy in detecting fake news. The results of the study confirm the important role of conspiracy thinking style in false news recognition (leading to a decrease in accuracy) and users’ capability for deliberation on social media more broadly. However, the influence of contextual factors is mixed. While news sources exhibit no influence on the accuracy of fake or true news detection, dominant framing tends to increase the accuracy of true news only. More predictors of news recognition accuracy are discussed in the paper. As a result, this research contributes to the theory of fake news susceptibility by revealing a rich set of individual factors and interaction effects that influence human judgment about news truthfulness and impact deliberation possibilities in socially mediated environments.

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Acknowledgements

The research was implemented in the framework of the Russian Scientific Fund Grant № 19–18-00206 at the National Research University Higher School of Economics (HSE) in 2021.

The authors acknowledge the research and data collection assistance by Maxim Terpilowski, Yadviga Sinyawskaya, and Victoria Vziatysheva.

Compliance with Ethical Standards. The authors declare that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (National Research University Higher School of Economics Institution Research Board decision, 23.04.2020).

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Authors and Affiliations

  1. National Research University Higher School of Economics, St. Petersburg, Russia

    Alexander Porshnev & Olessia Koltsova

  2. Bishop’s University, Sherbrooke, Canada

    Alex Miltsov

  3. Dublin City University, Dublin, Ireland

    Tetyana Lokot

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  1. Alexander Porshnev
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  2. Alex Miltsov
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  3. Tetyana Lokot
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  4. Olessia Koltsova
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Correspondence to Alexander Porshnev .

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

    Gabriele Meiselwitz

Appendix 1. Supplementary Material

Appendix 1. Supplementary Material

Supplementary tables associated with this article can be found, in the online version, at https://fakenewsproject.org/HCI2021/Appendix_1.pdf.

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Porshnev, A., Miltsov, A., Lokot, T., Koltsova, O. (2021). Effects of Conspiracy Thinking Style, Framing and Political Interest on Accuracy of Fake News Recognition by Social Media Users: Evidence from Russia, Kazakhstan and Ukraine. 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_23

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