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Record W2309147984 · doi:10.4018/joeuc.2016040103

The Influence of Social Presence, Social Exchange and Feedback Features on SNS Continuous Use

2016· article· en· W2309147984 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Organizational and End User Computing · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsHEC MontréalWestern University
Fundersnot available
KeywordsPerceptionVariance (accounting)PsychologyVariety (cybernetics)Social exchange theorySocial psychologySocial network (sociolinguistics)Information exchangeSocial influenceSocial mediaComputer scienceWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

Social network sites (SNS) are venues for information sharing that provide a variety of communication features capable of stirring emotions, attitudes and beliefs. This paper highlights the role of SNS feedback features and the meanings they communicate to their users, as design elements capable of enhancing the SNS experience. Based on the theories of Social Presence and Social Exchange, the study suggests and empirically validates a research model where Feedback, Perceived Social Presence, Attitude, Enjoyment and Perceived Usefulness are hypothesized to explain intentions to continue to use an SNS. The results of an online survey of 262 Facebook users found that feedback features were central SNS components that influenced perceptions of social presence and enjoyment, which in turn, along with attitude and perceived usefulness, influenced intentions to continue using Facebook, explaining 55% of its variance. The theoretical and practical implications of these results are discussed.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.537
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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