  From a computer science perspective, addressing on-line hate speech is a
challenging task that is attracting the attention of both industry (mainly
social media platform owners) and academia. In this chapter, we provide an
overview of state-of-the-art data-science approaches - how they define hate
speech, which tasks they solve to mitigate the phenomenon, and how they address
these tasks. We limit our investigation mostly to (semi-)automatic detection of
hate speech, which is the task that the majority of existing computer science
works focus on. Finally, we summarize the challenges and the open problems in
the current data-science research and the future directions in this field. Our
aim is to prepare an easily understandable report, capable to promote the
multidisciplinary character of hate speech research. Researchers from other
domains (e.g., psychology and sociology) can thus take advantage of the
knowledge achieved in the computer science domain but also contribute back and
help improve how computer science is addressing that urgent and socially
relevant issue which is the prevalence of hate speech in social media.
