A survey on extremism analysis using natural language processing: definitions, literature review, trends and challenges

Javier Torregrosa,David Camacho,Eugenio Martínez-Cámara,Javier Del Ser,Gema Bello-Orgaz

doi:10.1007/s12652-021-03658-z

Abstract

Extremism has grown as a global problem for society in recent years, especially after 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. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, 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 first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, 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 towards stimulating further research in this exciting research area.

Highlights

The rise of Social Media platforms has strengthened the interest of researchers for studying human behavior on different contexts, as they give them the chance of crawling real time data from the users, and stored or published data during long periods of time (Bayerl et al 2014)
Until now we have presented a distinction between the concepts of radicalization and extremism, choosing the latter as a key concept to justify the aims of this article
Different kind of movements, such as jihadi terrorism and far-right groups, have changed the political and social agenda of several countries, including hot topics that are discussed as relevant issues for those countries (Ali 2021)

Summary

Introduction

The rise of Social Media platforms has strengthened the interest of researchers for studying human behavior on different contexts, as they give them the chance of crawling real time data from the users, and stored or published data during long periods of time (Bayerl et al 2014). One of the area that has benefited of NLP techniques on recent years is the study of extremist discourse, due to the increasing use of Social Media by different extremist groups. Extremism can facilitate the justification of violent actions to achieve a movement’s agenda (Thomas 2012) This threat led different countries to finance research projects and other initiatives related to the study of the traces that extremists users left online, with the aim of identifying early behaviors to stop them before embracing violent extremism. Machine learning (ML) techniques made a great contribution to this purpose (see, for example Scanlon and Gerber 2014)

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