Duality of self-promotion on social networking sites
Bibliographic record
Abstract
Purpose Self-promotion on social networking sites (SNSs) is a controversial issue as it has been attributed to various positive and negative consequences. To better understand the reasons for the mixed consequences and the nature of self-promotion on SNSs, the purpose of this paper is to theorize and empirically investigate the duality of SNS self-promotion and its underlying socio-psychological mechanisms. Design/methodology/approach By drawing on the motivational affordance lens and self-determination theory, this study develops a theoretical account of the duality of self-promotion on SNSs. The author places subjective vitality and SNS addiction as the positive and negative consequences of self-promotion. The model was tested using partial least squares technique with data collected from 289 Finnish Facebook users using a survey. Findings The results show that self-promotion contributes to both subjective vitality and to SNS addiction. Importantly, exhibitionism attenuates the effect of self-promotion on subjective vitality and amplifies the effect of self-promotion on SNS addiction. The feature-level analysis shows that status updates, adding photos, commenting in others’ posts and profile completeness are the main determinants of self-promotion. Status updates, adding photos and check-ins, in turn, have high exhibitionistic appeal. Originality/value To date, the empirical attempts to investigate the duality of SNS use have been rare. In particular, prior research is largely silent in explaining what tilt the outcomes of self-promotion either toward positive or negative direction. The paper fills this theoretical and empirical gap and thus contributes to literature on dualities of SNS use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".