Disconnect between intentions and outcomes: A comparison of regretted text and photo social networking site posts
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.
Bibliographic record
Abstract
Many social networking site (SNS) users regret previous posts and post sensitive content despite the potential for negative consequences. Limited research has examined regret among SNS users, and it is unclear whether regret differs between text and graphic formats. An online survey of Australian SNS users (N = 995), compared regretted text to photo and video posts by examining demographic characteristics, psychological antecedents, post content, and consequences of posting. Feelings of regret were similar; however, regretted photo/video posts reported were related to a positive mood when posting, social motivations, and most frequently resulted in personal consequences (e.g., embarrassment). In comparison, regretted text posts were motivated by negative mood states and were more likely to result in social consequences. There might be a disconnection between what users hope to convey and how posts are perceived. SNS design that prompts users to consider the impacts of posts and to screen for offending content may reduce post regret. Interventions should encourage mindfulness of posting when upset and gaining self‐validation externally from SNS.
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 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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 it