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Record W4392852185 · doi:10.1177/20570473241234204

The rise of digital platforms as a soft power apparatus in the New Korean Wave era

2024· article· en· W4392852185 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

VenueCommunication and the Public · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSoft powerKorean WaveDigital eraPower (physics)TelecommunicationsHistoryElectrical engineeringComputer scienceEngineeringArtLiteraturePhysicsWorld Wide WebChinaArchaeologyThe Internet

Abstract

fetched live from OpenAlex

By employing digital soft power as a theoretical framework, this article examines the increasing role of domestic digital platforms in the New Korean Wave and their contributions to cultural diplomacy. It discusses the ways in which digital soft power becomes the primary vehicle in cultural diplomacy related to the Korean Wave. As there are tensions and conflicts between these private platforms and the Korean government, this article critically analyzes the crucial relations between these two major parties in executing cultural diplomacy and digital soft power. As its methodological framework, the utilization of social media by the Korean government, particularly by the Ministry of Foreign Affairs, was used. It selects the Ministry of Foreign Affairs’ Facebook posts between 1 January and 31 December of 2022 to determine the ways in which the Korean government utilizes social media as a soft power tool. It develops discourse analysis in tandem with the Ministry of Foreign Affairs’ Facebook posts to determine several major strategies the Korean government has advanced in the digital platform era.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.029
GPT teacher head0.301
Teacher spread0.272 · 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