Manipulation and abuse on social media
Not on the map. Why?
Abstract (arXiv)
The computer science research community has became increasingly interested in the study of social media due to their pervasiveness in the everyday life of millions of individuals. Methodological questions and technical challenges abound as more and more data from social platforms become available for analysis. This data deluge not only yields the unprecedented opportunity to unravel questions about online individuals' behavior at scale, but also allows to explore the potential perils that the massive adoption of social media brings to our society. These communication channels provide plenty of incentives (both economical and social) and opportunities for abuse. As social media activity became increasingly intertwined with the events in the offline world, individuals and organizations have found ways to exploit these platforms to spread misinformation, to attack and smear others, or to deceive and manipulate. During crises, social media have been effectively used for emergency response, but fear-mongering actions have also triggered mass hysteria and panic. Criminal gangs and terrorist organizations like ISIS adopt social media for propaganda and recruitment. Synthetic activity and social bots have been used to coordinate orchestrated astroturf campaigns, to manipulate political elections and the stock market. The lack of effective content verification systems on many of these platforms, including Twitter and Facebook, rises concerns when younger users become exposed to cyber-bulling, harassment, or hate speech, inducing risks like depression and suicide. This article illustrates some of the recent advances facing these issues and discusses what it remains to be done, including the challenges to address in the future to make social media a more useful and accessible, safer and healthier environment for all users.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Mar 2015.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1; 2026: 1.
6 papers.
- 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Modelscited by 144
- 2022Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trollscited by 8
- 2024IOHunter: Graph Foundation Model to Uncover Online Information Operationscited by 4
- 2025A Survey of Social Cybersecurity: Techniques for Attack Detection, Evaluations, Challenges, and Future Prospectscited by 1
- 2022Don't "research fast and break things": On the ethics of Computational Social Sciencecited by 0
- 2026A Social Media Analysis of Discourse on the Israel--Palestine Conflict on Telegramcited by 0
- 2026A Social Media Analysis of Discourse on the Israel--Palestine Conflict on Telegram17 Jul 2026
- 2025A Survey of Social Cybersecurity: Techniques for Attack Detection, Evaluations, Challenges, and Future Prospects6 Apr 2025
- 2024IOHunter: Graph Foundation Model to Uncover Online Information Operations19 Dec 2024
- 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models7 Apr 2023
- 2022Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls17 Oct 2022
- 2022Don't "research fast and break things": On the ethics of Computational Social Science12 Jun 2022