Psychological Predictors of Internet Social Communication
Bibliographic record
Abstract
This study investigated the relationship of traditional social behavior to social communication via the Internet in a completely wired campus where every professor uses computers in classroom teaching, each residence is wired to the Internet, and every student is issued a laptop computer. It has been suggested that shy and socially isolated individuals communicate more on the Internet because it provides some protection from social anxiety. However, little research has empirically tested this assumption. In line with social network theory, we proposed, instead, that online social communication would complement or supplement the uses of face-to-face social contact resulting in a positive association between the two forms of social behaviors. We assessed the frequency and intimacy of traditional social behaviors, sociability, and shyness in 115 undergraduates (52 male, 63 female). These variables were then used to predict the frequency and intimacy of Internet social communication. Sociability and the frequency of traditional social behaviors were positively associated with the frequency of Internet social communication. The intimacy of traditional social behaviors was positively associated with the intimacy of Internet social communication. Overall, the findings supported the implications of social network theory in that online social communication appeared to complement or be an extension of traditional social behavior rather than being a compensatory medium for shy and socially anxious individuals. With relation to uses and gratifications theory, however, shyness was associated with increased intimate socializing over the Internet, indicating that traditional and Internet communication are not functionally equivalent.
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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 | 0.001 | 0.011 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".