Identity and Narrative Persuasion: How ISIS Western-Directed Propaganda Works
Bibliographic record
Abstract
This study presents an identity-centered narrative theory of high-risk political activism to explain how narratives engage with social identities, and how variation in narratives can be strategically deployed by political actors to engage different mobilization pools. Narratives are stories that persuade through identification with plot and characters, with mobilization bringing expressive payoffs. Narratives tailored to identities maximizes their recruitment potential. Our empirical case is the Islamic State in Iraq and Syria’s Western-directed video recruitment campaign. We argue that ISIS’s use of tailored narratives explains its success in mobilizing diverse social identities within the community of Muslims living in the West. We present evidence for the theory from an online survey experiment with 139 US and Canadian Muslims and analyses of narratives in 16 ISIS propaganda videos and motives in 148 US ISIS perpetrators. The paper helps explain how appeals targeting identities can mobilize, including under circumstances of widespread social disapproval.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".