A Dual-Identity Perspective of Obsessive Online Social Gaming
Why this work is in the frame
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Bibliographic record
Abstract
Obsessive online social gaming has become a worldwide societal challenge that deserves more scholarly investigation. However, this issue has not received much attention in the information systems (IS) research community. Guided by dual-system theory, we theoretically derive a typology of obsessive technology use and contextually adapt it to conceptualize obsessive online social gaming. We also build upon identity theory to develop a dual-identity perspective (i.e., IT identity and social identity) of obsessive online social gaming. We test our research model using a longitudinal survey of 627 online social game users. Our results demonstrate that the typology of obsessive technology use comprises four interrelated types: impulsive use, compulsive use, excessive use, and addictive use. IT identity positively affects the four obsessive online social gaming archetypes and fully mediates the effect of social identity on obsessive online social gaming. The results also show that IT identity is predicted by embeddedness, self-efficacy, and instant gratification, whereas social identity is determined by group similarity, group familiarity, and intragroup communication. Our study contributes to the IS literature by proposing a typology of obsessive technology use, incorporating identity theory to provide a contextualized explanation of obsessive online social gaming and offering implications for addressing the societal challenge.
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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 | 0.002 | 0.006 |
| 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 | 0.002 |
| 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