Abstract
This multi-study paper demonstrates that large language model-generated social media posts (via GPT-4) outperform human-written messages in driving digital engagement. Using a dataset of Fortune 500 Twitter posts, Study 1 introduces and validates the FIIT model – Fluency, Interactivity, Information, and Tone – a linguistic framework explaining why AI-optimized content attracts more likes, comments, and shares. Study 2 experimentally confirms that consumers prefer AI-generated posts, while Study 3 shows that even trained public relations professionals, despite FIIT instruction and monetary incentives, cannot match AI performance. Together, these studies provide large-scale, multi-method evidence that generative AI can outperform human communicators in measurable engagement outcomes. The paper advances computational grounded theory in strategic communication and discusses implications for public relations practice, research, and education in the era of generative AI.
| Original language | English (US) |
|---|---|
| Article number | 102643 |
| Journal | Public Relations Review |
| Volume | 51 |
| Issue number | 5 |
| DOIs | |
| State | Published - Dec 2025 |
Bibliographical note
Publisher Copyright:© 2025 Elsevier Inc.
Keywords
- AI
- Brand communication
- Computational methods
- Generative AI
- GPT
- Public relations
- Social media engagement
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