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Assessing Violence Risk among Far-Right Extremists: A New Role for Natural Language Processing.

Julia Ebner1, Christopher Kavanagh1, Harvey Whitehouse1

  • 1Department of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK.

Terrorism and Political Violence
|September 11, 2024
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Summary
This summary is machine-generated.

Language analysis of extremist groups can detect risk factors for violent extremism. A new framework identifies linguistic markers indicating potential real-world violence, aiding early detection and prevention efforts.

Keywords:
Far-right extremismidentity fusionterrorismviolence risk assessmentviolent extremism

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Area of Science:

  • Psychology of extreme groups
  • Computational linguistics
  • Sociology of conflict

Background:

  • Willingness to fight for groups stems from fused personal and group identities.
  • Threatened groups, condoned violence, and dehumanization of enemies are key factors.
  • Early detection of violent extremism risk factors is crucial.

Purpose of the Study:

  • To investigate if extremist language can facilitate early detection of violent extremism risk factors.
  • To develop and apply a novel fusion-based linguistic violence risk assessment framework.
  • To analyze language patterns in far-right extremist online groups.

Main Methods:

  • Applied a fusion-based linguistic violence risk assessment framework.
  • Utilized R-based Natural Language Processing (NLP) analysis.
  • Developed a Violence Risk Index integrating linguistic markers from terrorist manifestos.
  • Compared risk scores of extremist groups with non-extremist controls.
  • Incorporated qualitative insights to contextualize findings.

Main Results:

  • Fusion markers and other linguistic variables accurately indicated real-world violence levels.
  • The NLP analysis produced a weighted risk assessment score for each group.
  • Significant linguistic markers differentiating violent from non-violent communiqués were identified.
  • Far-right extremist groups exhibited distinct language patterns.

Conclusions:

  • Linguistic analysis offers a promising avenue for detecting and preventing violent terrorism.
  • The fusion-based framework effectively identifies risk factors associated with violent extremism.
  • Language analysis can serve as an early warning system for potential violence.