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Record W2489188104 · doi:10.1080/09546553.2016.1207633

Video games, terrorism, and ISIS’s Jihad 3.0

2016· article· en· W2489188104 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTerrorism and Political Violence · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and Radicalism
Canadian institutionsConcordia University
Fundersnot available
KeywordsPublicityTerrorismIslamVideo gameDimension (graph theory)Social mediaMedia studiesPolitical scienceState (computer science)Online videoAdvertisingSociologyPublic relationsLawMultimediaHistoryComputer scienceBusiness

Abstract

fetched live from OpenAlex

This study discusses different media strategies followed by the Islamic State in Iraq and Syria (ISIS). In particular, the study attempts to understand the way ISIS’s video game that is called “Salil al-Sawarem” (The Clanging of the Swords) has been received by the online Arab public. The article argues that the goal behind making and releasing the video game was to gain publicity and attract attention to the group, and the general target was young people. The main technique used by ISIS is what I call “troll, flame, and engage.” The results indicate that the majority of comments are against ISIS and its game, though most of the top ten videos are favorable towards the group. The sectarian dimension between Sunnis and Shiites is highly emphasized in the online exchanges, and YouTube remains an active social networking site that is used by ISIS followers and sympathizers to promote the group and recruit others.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.292
Teacher spread0.280 · 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