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Record W2996022902 · doi:10.20527/jbsp.v9i2.7477

TINDAK TUTUR EKSPRESIF PUJIAN DAN CELAAN TERHADAP PEJABAT NEGARA DI MEDIA SOSIAL

2019· article· en· W2996022902 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

VenueJURNAL BAHASA SASTRA DAN PEMBELAJARANNYA · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Language Analysis
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsPraiseSarcasmSocial mediaHumanitiesPopularitySociologyIronyMedia studiesArtPsychologyLiteratureComputer scienceSocial psychologyWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Speech Acts of Praise and Mockery Expressions towards State Officials throughSocial Media. This research was conducted with the aim of describing the formsand funcion of speech acts praise and mockery expressions in Twitter, Instagram,and Facebook. The design of this research used descriptive research withqualitatve approach. The sources oh the data of this research were from the resultof observation in a social media twitter, instagram, and facebook. The formscategorized into praises in terms of the most frequent speakers encountered arepraises with the forms of interjection, praise of God, comparing, appreciating,showing off objects, and joking. Mockery expressions are in terms of speakersfound through social media which are often found in praises with apophasis,unuendo, irony, and sarcasm. In addition to aspects in the field of government, theobject of praises and mockery are: physical, religious, moral, mental, popularity,and integrity conditions. Key words: speech acts, praise expressions, mockery expressions Abstrak Tindak Tutur Ekspresif Pujian dan Celaan terhadap Pejabat Negara di MediaSosial. Penelitian ini dilaksanakan dengan tujuan mendeskripsikan bentuk danfungsi tindak tutur ekspresif pujian dan celaan di media twitter, instagram danfacebook. Penelitian ini menggunakan rancangan penelitian deskriptif denganpendekatan kualitatif. Sumber data penelitian ini berasal dari kumpulan data darimengobservasi media sosial twitter, instagram, dan facebook. Bentuk-bentukdikategorikan menjadi pujian dari segi penutur yang terdapat dalam media sosialyang banyak ditemui adalah pujian dengan bentuk interjeksi, pujian kepada tuhan,membandingkan, mengapresiasi, membanggakan objek, dan kelakar. Tindak tuturcelaan dari segi penutur yang terdapat dalam media sosial yang banyak ditemuiadalah pujian dengan bentuk apofasis, unuendo, ironi, dan sarkasme. Selain aspekdibidang pemerintahan, yang menjadi objek pujian dan celaan, yaitu kondisi fisik,religi, moral, mental, popularitas, dan integritas. Selain aspek dibidangpemerintahan, yang menjadi objek pujian dan celaan, yaitu kondisi fisik, religi,moral, mental, popularitas, dan integritas. Kata-kata kunci: tindak tutur, ekspresif pujian, ekspresif celaan

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.215
Teacher spread0.203 · 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