Social Media Presence and Organizational Performance: An Empirical Study on Companies’ Presence on Twitter
Bibliographic record
Abstract
Social media has garnered increased attention amongst individuals and organizations. At organizational levels, social media gives companies a way to connect with the market in a real-time manner. It becomes an essential component of marketing and business. However, the economic advantage of the presence of companies on social media platforms remains hardly studied. In this research, we focus on the economic relevance of being on social media, and more specifically on Twitter, at firm levels. With a sample of 227 Canadian companies listed on the Toronto Stock Exchange (TSX), we analyze the relationship between corporate performance and the company’s presence on Twitter. Our results suggest that companies can realize a competitive advantage in having social media presence. Indeed, companies that are active on Twitter stand out for their performance; either we measure corporate performance by stock market performance or by return on assets (ROA). Our results highlight the benefits of being active on social media.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".