
TL;DR
This paper surveys ten years of research on social bot detection, highlighting key trends, achievements, and ongoing challenges, and proposes future directions to combat online deception and manipulation effectively.
Contribution
It provides a comprehensive longitudinal analysis of social bot detection research, identifying major developments and suggesting innovative strategies for future efforts.
Findings
Research has evolved from basic detection methods to sophisticated, adaptive techniques.
Major achievements include improved accuracy and understanding of bot behaviors.
Challenges remain due to evolving deception tactics and the complexity of social media environments.
Abstract
On the morning of November 9th 2016, the world woke up to the shocking outcome of the US Presidential elections: Donald Trump was the 45th President of the United States of America. An unexpected event that still has tremendous consequences all over the world. Today, we know that a minority of social bots, automated social media accounts mimicking humans, played a central role in spreading divisive messages and disinformation, possibly contributing to Trump's victory. In the aftermath of the 2016 US elections, the world started to realize the gravity of widespread deception in social media. Following Trump's exploit, we witnessed to the emergence of a strident dissonance between the multitude of efforts for detecting and removing bots, and the increasing effects that these malicious actors seem to have on our societies. This paradox opens a burning question: What strategies should we…
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