Psychological factors related to self‐disclosure and relationship formation in the online environment
Bibliographic record
Abstract
Abstract The current research constructs a measure of one's willingness to form online relationships and disclose personal and private information and examines how this measure relates to personality and individual differences. In Study 1, we developed a measure to assess one's Openness to Form Online Relationships (OFOR). Two factors emerged: Engagement and Suspicion. Results indicated that individuals who reported higher OFOR Engagement also self‐reported higher self‐concealment and self‐monitoring and lower Honesty‐Humility and Conscientiousness. In Study 2, we examined the extent to which our measures and the OFOR related to people's actual willingness to share personal information. Higher OFOR Engagement was related to greater disclosure. In addition, self‐concealment and the Dark Triad were significantly related to the severity and privacy of self‐disclosure. The current research constructs a new measure of and provides insight into some of the individual differences and personality traits involved in a person's openness to form relationships online and his/her willingness to disclose private information. This work contributes to our understanding of the factors that may make some individuals vulnerable to being deceived by others in the online environment. This work can be used to inform training or messaging to increase community resilience against deception, such as online scams.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".