  Extremism research has grown as an open problem for several countries during
recent years, especially due to the apparition of movements such as jihadism.
This and other extremist groups have taken advantage of different approaches,
such as the use of Social Media, to spread their ideology, promote their acts
and recruit followers. Natural Language Processing (NLP) represents a way of
detecting this type of content, and several authors make use of it to describe
and discriminate the discourse held by this groups, with the final objective of
detecting and preventing its spread. This survey aims to review the
contributions of NLP to the field of extremism research, providing the reader
with a comprehensive picture of the state of the art of this research area. The
content includes a description and comparison of the frequently used NLP
techniques, how they were applied, the insights they provided, the most
frequently used NLP software tools and the availability of datasets and data
sources for research. Finally, research questions are approached and answered
with highlights from the review, while future trends, challenges and directions
derived from these highlights are suggested.
