Drivers of firms’ sociability on social media: Evidence from an emerging country
Bibliographic record
Abstract
The purpose of this paper is to investigate the drivers of firms’ sociability on social media (SM), an unregulated area, in an emerging country, namely, Kingdom of Saudi Arabia (KSA). The sample of this study is 345 non-financial listed firms on Tadawul stock exchange during 2016-2019. Data are collected from several sources such as annual reports, the official website of the sample companies. Other data are collected manually such as the presence of the CEO and the sampled companies on SM. Our findings show that firm size and leverage level are important firms’ characteristics that drive firms’ sociability on social media. The finding shows that CEO sociability on social media is a key CEOs’ characteristic that drives firms’ sociability on social media. Further analysis reports that there is a complementary effect between CEO’s sociability on social media and firm size in increasing firms’ sociability on SM. The findings also show that there is a complementary effect between CEO’s sociability on social media and firm leverage in increasing firms’ sociability on SM. This study contributes to the disclosure literature by providing empirical evidence of the drivers of firms’ sociability on SM, an unregulated area in KSA. It also complements the considerable literature on voluntary disclosure which ignores the use of SM platforms as a “new” voluntary type of reporting. The present study complements recent literature on the adoption of SM by providing evidence that the sociability of top leaders is a driver of firms’ sociability on SM.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.004 | 0.001 |
| 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".