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Record W2946910923 · doi:10.5539/ass.v15n6p1

The Communication Ethics of WeChat Public Platforms

2019· article· en· W2946910923 on OpenAlexvenueno aff
Ranni Zhang, Qiqi Zhong, Songping Yang, Boya Wang

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
FundersJinan University
KeywordsDisseminationPhenomenonPublic relationsMisconductPublic opinionOrder (exchange)Path (computing)Information and Communications TechnologyPolitical scienceInternet privacySociologyBusinessComputer scienceLawEpistemology

Abstract

fetched live from OpenAlex

In the new media era, the information is updating each passing day. Although the official communication of college education is carried out efficiently by the platform of WeChat public account, it is interfered by its muddy information, the abuse of freedom of speech and rumors spreads. This phenomenon leads to the moral misconduct and the marginalization of the legal system. It is imperative to build the communication ethics and norms of Wechat public platform in Colleges and universities. The significance of the construction of the WeChat public platform communication theory and regulations from the perspectives of disseminating the correct orientation of public opinion is discussed in this paper, in order to improve the communication information literacy of netizens and meet the need of network supervision system, and suggest the path for exploring correlative strategy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.025
Scholarly communication0.0100.008
Open science0.0010.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.399
Teacher spread0.324 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2019
Admission routes1
Has abstractyes

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