MétaCan
Menu
Back to cohort

The Effects of Virtual Likes on Self-Esteem

2022· book-chapter· en· W4286593352 on OpenAlexaff
Malinda Desjarlais

Bibliographic record

VenueIGI Global eBooks · 2022
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsMount Royal University
Fundersnot available
KeywordsSelf-esteemPsychologySocial psychologyValue (mathematics)Social comparison theoryComputer science

Abstract

fetched live from OpenAlex

Social networking sites offer opportunities for users to express themselves and receive immediate feedback in the form of virtual likes. Adolescents place a great deal of value on the number of likes, regarding them as indicators of peer acceptance and support. Since peer feedback and social comparison are integral to adolescents' self-evaluations, the aim of the current chapter is to determine whether self-esteem is sensitive to the number of likes associated with their own (peer feedback) and others' posts (social comparison). The synthesis of literature indicates that self-esteem is responsive to indicators of one's value to others as well as the value of others, supporting the sociometer and social comparison theories. Indications of liking online serve to enhance self-esteem, whereas rejection deflates it. In addition, seeing others get many likes negatively impacts viewers' self-esteem. The gaps in the literature are discussed and future research is suggested.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.018
GPT teacher head0.235
Teacher spread0.218 · 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 designObservational
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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueIGI Global eBooksSame topicMedia Influence and HealthFrench-language works237,207