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Record W2580297071 · doi:10.3968/9015

The Impact of Social Media on Conventional Journalism Practice in Nigeria: A Study of Journalists’ in Jalingo Metropolis

2016· article· en· W2580297071 on OpenAlexvenueno aff
Oberiri Destiny Apuke

Bibliographic record

VenueCanadian social science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsJournalismSocial mediaData collectionThe InternetSample (material)PopulationSociologySimple random samplePublic relationsMedia studiesPsychologyPolitical scienceAdvertisingSocial scienceBusinessComputer scienceWorld Wide WebLaw

Abstract

fetched live from OpenAlex

This study examines the impact of social media on journalism practice in Nigeria. It explores the extent to which social media has changed journalism practice in Nigeria with special reference to Journalists in Jalingo metropolis. The quantitative survey method was adopted for the study. The population is comprised of 293 Journalists in Jalingo metropolis registered under Nigerian  Union of Journalists. The study employed Taro Yame’s formula to sample out 75 journalists. Questionnaires were used as the tool for data collection. The researcher administered questionnaires to 75 purposively selected Journalists, and 70 were duly answered and retrieved. Data gathered were analyzed with SPSS version 20 with devices such as frequency counts and simple percentages. Data analyzed were presented in tables. Findings revealed among other things that a considerable number of journalists in Jalingo metropolis are computer literate, and they have internet access at various levels. Findings also revealed that journalists in Jalingo metropolis go online very often and that they prefer Facebook to other forms of social media and this assist them in faster gathering and dissemination of news. The study recommends among other things that Journalists should conduct researches on the accessible online networking organizing apparatuses to check which one of them is more and solid, keeping in mind the end goal to guarantee the validity of sources.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.038
GPT teacher head0.384
Teacher spread0.345 · 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.

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

Citations7
Published2016
Admission routes1
Has abstractyes

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