IDENTIFYING SOCIAL COMPUTING DIMENSIONS : A MULTIDIMENSIONAL SCALING STUDY
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
Despite an increasing popularity, the impact and benefits of corporate social computing remain unclear. This paper aims at rigorously studying social computing tools as a new class of technology and provides a holistic definition and characterization. After a comprehensive literature review, we empirically explored the defining attributes and underlying dimensions of social computing as a whole using the multidimensional scaling (MDS) methodology. The study found that 13 representative exemplar tools differ over three dimensions: (i) their ability to support social interactions, social relations, and communities, (ii) their hedonic versus utilitarian focus, and (iii) their ability to support convergence versus conveyance of generated content. A Property Fitting (ProFit) study confirmed the interpretation of the dimensions. This provided a better understanding of this technology and allowed us to better theorize about the expected benefits and impacts of social computing on organizations, to offer guidelines for adoption and provide suggestions for future research.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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