A Decade of Social Bot Detection
- URL: http://arxiv.org/abs/2007.03604v2
- Date: Wed, 8 Jul 2020 07:55:22 GMT
- Title: A Decade of Social Bot Detection
- Authors: Stefano Cresci
- Abstract summary: In the aftermath of the 2016 US elections, the world started to realize the gravity of widespread deception in social media.
What strategies should we enforce in order to stop this social bot pandemic?
What stroke social, political and economic analysts after 2016, deception and automation, has been however a matter of study for computer scientists since at least 2010.
- Score: 0.9137554315375922
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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 enforce in order to stop
this social bot pandemic? In these times, during the run-up to the 2020 US
elections, the question appears as more crucial than ever. What stroke social,
political and economic analysts after 2016, deception and automation, has been
however a matter of study for computer scientists since at least 2010. In this
work, we briefly survey the first decade of research in social bot detection.
Via a longitudinal analysis, we discuss the main trends of research in the
fight against bots, the major results that were achieved, and the factors that
make this never-ending battle so challenging. Capitalizing on lessons learned
from our extensive analysis, we suggest possible innovations that could give us
the upper hand against deception and manipulation. Studying a decade of
endeavours at social bot detection can also inform strategies for detecting and
mitigating the effects of other, more recent, forms of online deception, such
as strategic information operations and political trolls.
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