Off the Court: Examining Social Media Activity and Engagement in Women’s Professional Sport
Bibliographic record
Abstract
Sports organizations’ use of social media (SM) has become a key strategy in the coverage and promotion of sport. Although research has been done on the success of digital marketing for men’s professional sport, little is known about the impact of such in women’s sport. This study aimed to examine the SM activity and engagement with fans of the Women’s National Basketball Association. All posts from Facebook, Instagram, and Twitter for the 2019 calendar year were collected from all 12 Women’s National Basketball Association teams and analyzed, in aggregate, for their SM metrics. Results indicated that there was a high level of interaction on SM during the in-season competition months, whereas engagement during the off-season period declined. Given these results, the Women’s National Basketball Association should create strategies to increase fan engagement when there is decreased interactivity to perpetually promote women’s sport. This research provides a starting point for future research on women’s sport involving SM metrics.
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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 | 0.006 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".