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Record W1965950838 · doi:10.5539/ass.v11n10p86

Social Media as a New Trend in Sri Lankan Digital Journalism: A Surveillance

2015· article· en· W1965950838 on OpenAlexvenueno aff
Selvarajah Thuseethan, Shanmuganathan Vasanthapriyan

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsJournalismSocial mediaDigital mediaContext (archaeology)Sri lankaCitizen journalismSociologyPublic relationsMedia studiesPolitical scienceComputer scienceGeographyWorld Wide WebSocioeconomics

Abstract

fetched live from OpenAlex

In the last five years the rapid growth of social media that has been observed is indicative of its importance and its integration into the daily lives of many people in Sri Lanka. In parallel with this, there has also been considerable growth in digital journalism through the online medium. But the reachability of social media is very much high with comparing the traditional online mediums. As the result social media is converted as an online news media and overcomes the existing media in digital journalism. This pilot study explores the new trend in digital journalism with the presence of social media and carries out empirical research to understand the effectiveness of social media as a news medium and an effort has been made to propose expansion strategies of social media in maximizing the effectiveness in future digital journalism in the Sri Lankan context.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.802
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.054
GPT teacher head0.361
Teacher spread0.307 · 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 teacher head, 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

Citations12
Published2015
Admission routes1
Has abstractyes

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