GOSIP in Cyberspace: Conceptualization and Scale Development for General Online Social Interaction Propensity
Bibliographic record
Abstract
The interactive nature of the Internet has boosted online communication for both social and business purposes. However, individual consumers differ in their predisposition to interact online with others. Whereas an impressive stream of research has investigated media interactivity, the existence of individual differences in the use of different online media, that is, differences in general online social interaction propensity, has so far received less research attention. An individual's predisposition to interact online affects many important consumer behaviors, such as online engagement and participation. Thus, in this paper, we propose and conceptualize general online social interaction propensity as a trait-based individual difference that captures the differences between consumers in their predisposition to interact with others in an online environment. Based on eight studies, we develop and validate a scale for measuring general online social interaction propensity and demonstrate its usefulness in understanding diversity in levels of engagement and in predicting online interaction behaviors. •Consumers differ in their predisposition to enter in online communication.•We conceptualize an individual difference trait termed GOSIP.•We empirically develop and validate a scale to measure GOSIP.•We show GOSIP's importance as antecedent of engagement and online behavior.•Interactive marketers can use GOSIP to assess consumer differences in online behavior.
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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 | 0.000 |
| 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 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".