The Impact of Social Media Salience on the Subjective Value of Social Cues
Bibliographic record
Abstract
Like face-to-face interactions, evidence shows that interacting on social media is rewarding. However, the rewards associated with social media are subject to unpredictable delays, which may shape how they are experienced. Specifically, these delays might enhance the subjective desirability of social rewards and subsequent reward-seeking behavior by sensitizing people to the presence of such rewards. Here, we ask whether thinking about a recent social media post or conversation influences the subjective value of monetary and social rewards. Across two studies, we find that individuals who are thinking about a recent social media post are more likely to sacrifice small financial gains for the chance to see a genuine smile (a social reward) compared with those who are thinking about a recent conversation. This suggests that rather than satisfying social needs, thinking about social media interactions enhances the subjective value of social rewards, potentially explaining the incentive value of social media.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".