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Record W4311784951 · doi:10.5267/j.ijdns.2022.12.004

We are cyborgs: The role of narcissism and self-esteem to become social media and tourism addicts

2022· article· en· W4311784951 on OpenAlexvenueno aff
Usep Suhud, Mamoon Allan, Dorojatun Prihandono, Terrylina Arvinta Monoarfa

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsNarcissismAddictionTourismPsychologySocial mediaStructural equation modelingSelf-esteemAffect (linguistics)Social psychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

It is argued that excessive social media use can lead to an addiction. This study compares two proposed research models. The first model examines how social media addiction, narcissism, and self-esteem affect tourism addiction. Whilst the second model studies the impact of narcissism and self-esteem on social media and tourist addiction. There were also two research models proposed here. Data collection was obtained in Jakarta, with 214 participants chosen by using the convenient sampling method. Exploratory factor analysis and structural equation models were used to process the data. Social media addiction and narcissism affect self-esteem, while social media addiction and tourist addiction affect self-esteem. This research combines the study of addiction, modern media, and cyber marketing.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.022
GPT teacher head0.305
Teacher spread0.283 · 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 designOther design
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

Citations11
Published2022
Admission routes1
Has abstractyes

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