Towards a conceptual framework for managing social media in enterprise online communities
Bibliographic record
Abstract
Enterprise online communities exist as vendor-hosted platforms to bridge customers, business partners, and employees to co-create values by supporting business objectives and client goals. Unfortunately, establishing online presence through the use of a community platform is no longer sustainable in this hyper-social world, as minimal competitive advantage can be achieved without continuous strategic planning. In an effort to break through the barriers inherent with growing online communities, we investigated the impact of emergent social media as a strategic enabler for attracting, fostering and sustaining community members. We developed a social media maturity model aimed at evaluating the extent of social media usage in an online community. This paper presents our continuing research on the proposed maturity model which is composed of 8 success clusters: communication; collaboration; personalization; externalization; governance; monitoring; technology; and, platform support. Preliminary results are discussed to reveal the utility of the proposed model and future research.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".