Professionally-Oriented Social Network Sites and the Need for Self-Promotion: The role of Profile Features.
Bibliographic record
Abstract
In recent years, with the widespread use of professionally-oriented social network sites (P-SNSs) such as LinkedIn, we have witnessed people increasingly use such sites for networking. Online networking can be done more efficiently than in-person networking because P-SNSs allow people to cross the boundaries of time and location and maintain and form relationships with more contacts with minimum costs. One's profile in P-SNSs plays a crucial role in online networking by facilitating relationship development and affording self-promotion. Building upon the needs–affordances–features perspective on social media, this research aims to answer how individuals' needs for self-promotion can be fulfilled by profile features in P-SNSs. Using an online survey of 120 LinkedIn users, this study finds that individuals’ need for self-promotion on P-SNSs is significantly associated with leveraging the self-presentation affordance (enabled by profile features) in these sites. However, the need for self-promotion is not significantly associated with some profile features. Keywords: Professionally-oriented social network sites, profile features, online networking, self-promotion, social media affordances, LinkedIn
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".