Social Media Use Predicts Greater Liking in In-Person Initial Interactions
Bibliographic record
Abstract
Does how people generally engage with their online social networks relate to offline initial social interactions? Using a large-scale study of first impressions ( N = 806, N dyad = 4,565), we examined how different indicators of social media use relate to the positivity of dyadic in-person first impressions, from the perspective of the participants and their interaction partners. Many forms of social media use (e.g., Instagram, Snapchat, passive) were associated with liking and being liked by others more, although some forms of use (e.g., Facebook, active) were not associated with liking others or being liked by others. Furthermore, most associations held controlling for extraversion and narcissism. Thus, while some social media use may be generally beneficial for offline social interactions, some may be unrelated, highlighting the idea that how, rather than how much, people use social media can play a role in their offline social interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".