Creating an Investigative Framework for Understanding and Investigating the Language Profiles in Lone Actor Terrorist Manifestos

  • Alice Siggery

Student thesis: Doctoral Thesis


Lone actor terrorism is deemed a growing threat, and due to the nature of lone actor terrorism, perpetrators are considered fiendishly hard to detect and disrupt before an attack takes place. Previous attempts to profile lone actor terrorists have either generated stereotypes of potential offenders or inconclusive precursor behavioural factors. A phenomenon identified among lone actor terrorists is the development of a manifesto released before an attack occurs. While previous profiling methods of behaviour have been inconclusive, profiling methods of the language used in lone actor terrorist manifestos can provide psychological insights which can be used in an investigative framework.

This thesis therefore aimed to investigate the language used within lone actor terrorist manifestos and identify language typologies that can be used in an investigative framework. The thesis comprises four exploratory studies considering the current methods of language analysis, language variable development, language typologies, and the development of an investigative framework. The research used a mixed methods approach for data analysis, with 19 lone actor terrorist manifestos analysed using qualitative methods. The resulting language data was further analysed using quantitative methods, and the combined results were used to develop an investigative framework.

The results identified three distinct language typologies within lone actor terrorist manifestos, with 89% of the lone actor terrorist case studies being categorised into a single language typology. The language typology data was used to develop the Lone Actor Terrorism Joint Analysis Method (LATJAM) framework. The LATJAM framework can be used to investigate and profile the language typologies found within lone actor terrorist language. The implications, applications, and areas for future research are also discussed.
Date of Award14 Sep 2023
Original languageEnglish
SupervisorDanny Hunt (Main Supervisor) & Calli Tzani Pepelasi (Co-Supervisor)

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