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The responsibility of social media in times of societal and political manipulation

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  • Reisach, Ulrike

Abstract

The way electorates were influenced to vote for the Brexit referendum, and in presidential elections both in Brazil and the USA, has accelerated a debate about whether and how machine learning techniques can influence citizens’ decisions. The access to balanced information is endangered if digital political manipulation can influence voters. The techniques of profiling and targeting on social media platforms can be used for advertising as well as for propaganda: Through tracking of a person's online behaviour, algorithms of social media platforms can create profiles of users. These can be used for the provision of recommendations or pieces of information to specific target groups. As a result, propaganda and disinformation can influence the opinions and (election) decisions of voters much more powerfully than previously.

Suggested Citation

  • Reisach, Ulrike, 2021. "The responsibility of social media in times of societal and political manipulation," European Journal of Operational Research, Elsevier, vol. 291(3), pages 906-917.
    • Handle: RePEc:eee:ejores:v:291:y:2021:i:3:p:906-917
    DOI: 10.1016/j.ejor.2020.09.020
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    Cited by:

    1. Stéphanie Camaréna, 2021. "Engaging with Artificial Intelligence (AI) with a Bottom-Up Approach for the Purpose of Sustainability: Victorian Farmers Market Association, Melbourne Australia," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    2. Jingtao Yi & Jiatao Li & Liang Chen, 2023. "Ecosystem social responsibility in international digital commerce," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(1), pages 24-41, February.
    3. Timothy M. Devinney & Christopher A. Hartwell & Jennifer Oetzel & Paul Vaaler, 2023. "Managing, theorizing, and policymaking in an age of sociopolitical uncertainty: Introduction to the special issue," Journal of International Business Policy, Palgrave Macmillan, vol. 6(2), pages 133-140, June.
    4. Kumar, Ajay & Taylor, James W., 2024. "Feature importance in the age of explainable AI: Case study of detecting fake news & misinformation via a multi-modal framework," European Journal of Operational Research, Elsevier, vol. 317(2), pages 401-413.
    5. Roger D. Magarey & Thomas M. Chappell & Kayla Pack Watson, 2024. "Investigating the Effects of Misinformation as Infopathogens: Developing a Model and Thought Experiment," Social Sciences, MDPI, vol. 13(6), pages 1-16, May.
    6. Andreea Nistor & Eduard Zadobrischi, 2022. "The Consumption Analysis of Economic Media at the Regional Level in a Developing Country," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    7. Seddigh, Mohammad Reza & Targholizadeh, Aida & Shokouhyar, Sajjad & Shokoohyar, Sina, 2023. "Social media and expert analysis cast light on the mechanisms of underlying problems in pharmaceutical supply chain: An exploratory approach," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Pervaiz Akhtar & Arsalan Mujahid Ghouri & Haseeb Ur Rehman Khan & Mirza Amin ul Haq & Usama Awan & Nadia Zahoor & Zaheer Khan & Aniqa Ashraf, 2023. "Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions," Annals of Operations Research, Springer, vol. 327(2), pages 633-657, August.

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