期刊
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
卷 -, 期 -, 页码 -出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12652-021-03658-z
关键词
Natural language processing; Radicalization; Extremism; Machine learning; Deep learning
类别
资金
- CRUE-CSIC agreement
- Springer Nature
This article discusses the issue of extremism as a global problem and explores the application of natural language processing (NLP) in extremism research. The article reviews the definition of extremism, the characteristics of extremist discourse, and the application and achievements of NLP techniques. It also suggests future research directions and challenges in this field.
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.
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