MétaCan
Menu
Back to cohort
Record W2791416177 · doi:10.5539/ass.v14n4p136

CPNT Model Analysis on New Media and “Gangnam Style”

2018· article· en· W2791416177 on OpenAlexvenueno aff
Kim Yong Kyoung

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Mobility and Location-Based Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStyle (visual arts)AdvertisingVariety (cybernetics)Key (lock)Popular musicMedia studiesSociologyComputer scienceArtVisual artsArtificial intelligenceBusiness

Abstract

fetched live from OpenAlex

PSY’s “GangNam Style” got the most views on various search engines for music around the world in 2012. The world has tremendously caught on the “GangNam Style” across borders regardless of race, nation and culture. “Oppa GangNam Style”, this lyric of the song by a funny Korean singer who looks fat with sunglasses has been hummed everywhere over the world. Main interest of people also has focused on this song recently. The song, “GangNam Style”, enraptured the world in a few months. A music video of “GangNam Style” was a huge hit on a great variety of video websites as well. Take “YouTube”, the most famous websites in the world, for an example. On this websites, PSY’s music video got about 1.8 billion views. It was listed as the largest number of “like” clicks on YouTube in the Guinness Book of World Record. Therefore, this article analyzes this case on the spread of PSY’s “GangNam Style” through the new mass media in order to determine reasons to hit the world as well as backgrounds to be popular. Due to this research, we can expect to predict a future trend of international spread through the new media.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0030.003
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 head0.027
GPT teacher head0.326
Teacher spread0.299 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicHuman Mobility and Location-Based AnalysisFrench-language works237,207