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Record W3082465244 · doi:10.1080/21670811.2020.1805779

Dimensions of Social Media Logics: Mapping Forms of Journalistic Norms and Practices on Twitter and Instagram

2020· article· en· W3082465244 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

VenueDigital Journalism · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJournalismSocial mediaRhetorical questionNormalization (sociology)SociologyIntentionalityNews mediaPublic relationsMedia studiesEpistemologyComputer sciencePolitical scienceSocial scienceWorld Wide WebLinguistics

Abstract

fetched live from OpenAlex

More than a decade of research in journalism studies on social media has examined how journalists and news organizations have adopted and/or adapted to Twitter, Facebook, Instagram, and more, surfacing tensions over professional control and normalization. This article advances a conceptual framework for analyzing forms of journalistic norms and practices on social media that takes as its starting point the nature of its platforms, specifically Twitter and Instagram, proposing five analytical dimensions to investigate journalism on social media. They are: 1) structure and design; 2) aesthetics; 3) genre conventions; 4) rhetorical practices; and 5) interaction mechanisms and intentionality. The accounts of five Chilean journalists are used to illustrate how these five dimensions work in the two platforms.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.111
GPT teacher head0.345
Teacher spread0.234 · 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