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Record W7111138133 · doi:10.25949/29896715

Online Extremist Ecosystems: How a Network of Platforms and Devices Shape Far-Right and Involuntary Celibate Extremism and Violence

2025· dissertation· W7111138133 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMacquarie University · 2025
Typedissertation
Language
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsSociotechnical systemEmpirical researchSocial mediaThematic analysisViolent extremismTerrorismNarrativeDigital mediaThe Internet

Abstract

fetched live from OpenAlex

This doctoral thesis by publication critically explores and sought to improve the adoption of ecological concepts and terms in extremism and terrorism studies, focusing on networked digital technologies and their capacity to influence the expression of or involvement in online extremist communities related to far-right and incel ideologies. The objective is to provide a foundational theoretical and empirical assessment of the use of ecology in extremism and terrorism studies. This research aims to provide theoretical and empirical support for future research or interventions concentrated on understanding and addressing the anticipated influence of networked digital media environments on involuntary celibacy and far-right extremist communities. The research questions guiding this research are: 1. What are the advantages and limitations of using ecology to understand and address far-right or incel online violent extremism?; and 2. In what ways do digital media environments (constituted by social media platforms and hardware devices) shape an individual’s involvement in far-right or incel OVEC? The study adopted an interdisciplinary, mixed-methods approach which combined methodological elements from social and ecological sciences, and produced a sociotechnical framework to better understand the social and technical relationships within online communities that involve far-right and incel extremism. This research compared different national and ideological online communities to identify commonalities, idiosyncrasies, and factors contributing to their respective emergence and evolution. Its research design is composed of combinations of qualitative and quantitative methods, such as narrative and thematic analysis, network analysis, and statistical modelling to analyse stories, identities, masculinities, and emotional expressions that enable the formation and maintenance of these communities as characterised by technology. Findings reveal ten concepts common to the form and function of ecosystems and ten foundational theoretical and methodological advantages and limitations of using ecological concepts and methods in extremism and terrorism research. The metaphorical use of ecosystems is mostly devoid of the abundant list of concepts core to the meaning of “ecosystems”, including (but not limited to): network; dynamism; complexity; classification; self-organisation; evolution; adaptation; swarm intelligence; non-linear behaviour; and emergence. At the time of this thesis’ writing, an “online extremist ecosystem” has been neither conceptualised nor theorised in any rigorous or consistent manner. This research advances the interdisciplinary uses of ecological concepts and terms in social sciences, specifically studies in terrorism and extremism and media and communication studies. This research produced important contextual information on the threat landscape within Australia and Canada concerning far-right extremism, and the threat landscape internationally concerning incel extremism. It contributed the first comprehensive socioecological assessment of how technologies facilitate conditions favourable to far-right and incel ideologies or identities as expressed in international online space. This study progressed understandings about how community behaviour and structural pressures can coalesce in “online extremist ecosystems” to characterise an individual’s involvement in far-right or incel online (violent) extremist communities. Outcomes of this thesis can directly contribute to policy and practice designs when implementing an interpersonal, measurable, sociotechnical intervention to address clients referred for their online extremist activities. Findings strongly support the idea that digital media technologies not only enable a violent extremist’s intention to action beliefs, but simultaneously shapes these intentions and beliefs. This thesis contributed a foundational theoretical and empirical knowledge base to advance interdisciplinary research and policy production concerning communities where far-right and incel extremists dwell and develop, and where violent extremism emerges as a result.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.243
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it