MétaCan
Menu
Back to cohort
Record W2136937406 · doi:10.1177/0093650210365537

Attitudes Toward Online Social Connection and Self-Disclosure as Predictors of Facebook Communication and Relational Closeness

2010· article· en· W2136937406 on OpenAlexaff
Andrew M. Ledbetter, Joseph P. Mazer, Jocelyn M. DeGroot, Kevin R. Meyer, Yuping Mao, Brian Swafford

Bibliographic record

VenueCommunication Research · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsClosenessSelf-disclosurePsychologySocial psychologyConnection (principal bundle)Social mediaSocial network (sociolinguistics)WarrantAssociation (psychology)Computer-mediated communicationSocial anxietyThe InternetAnxietyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This investigation tested a theoretical model of communication behavior with specific Facebook friends, such that attitudes toward (a) online self-disclosure, and (b) online social connection, predict Facebook communication frequency and, in turn, relational closeness. Participants included both undergraduates and older adults. Results generally supported the model, with the interaction effect between self-disclosure and social connection directly predicting Facebook communication and indirectly predicting relational closeness. For both dependent variables, online social connection was a positive predictor at low and moderate levels of online self-disclosure, but high levels reduced the association to nonsignificance. One implication of these results was that high-warrant information may discourage those with social anxiety from social network site communication.

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)0.002
metaresearch head score (Gemma)0.012
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.443
Teacher spread0.346 · 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

Citations347
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCommunication ResearchSame topicImpact of Technology on AdolescentsFrench-language works237,207