  The issue of quantifying and characterizing various forms of social media
manipulation and abuse has been at the forefront of the computational social
science research community for over a decade. In this paper, I provide a
(non-comprehensive) survey of research efforts aimed at estimating the
prevalence of spam and false accounts on Twitter, as well as characterizing
their use, activity, and behavior. I propose a taxonomy of spam and false
accounts, enumerating known techniques used to create and detect them. Then, I
summarize studies estimating the prevalence of spam and false accounts on
Twitter. Finally, I report on research that illustrates how spam and false
accounts are used for scams and frauds, stock market manipulation, political
disinformation and deception, conspiracy amplification, coordinated influence,
public health misinformation campaigns, radical propaganda and recruitment, and
more. I will conclude with a set of recommendations aimed at charting the path
forward to combat these problems.
