# User Negotiations of Authenticity, Ownership, and Governance on AI-Generated Video Platforms: Evidence from Sora

arXiv: https://arxiv.org/abs/2512.05519 · HTML: https://mlsanity.com/paper/2512.05519/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 45 references that are in the map.
- First posted on arXiv 5 Dec 2025.

## Builds on (most cited first, 10 of 10)

- [Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models](https://mlsanity.com/paper/2402.17177/) (2024)
- [Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting](https://mlsanity.com/paper/2303.03199/) (2023)
- [PromptCARE: Prompt Copyright Protection by Watermark Injection and Verification](https://mlsanity.com/paper/2308.02816/) (2023)
- [Understanding the Impact of AI Generated Content on Social Media: The Pixiv Case](https://mlsanity.com/paper/2402.18463/) (2024)
- [Sora OpenAI's Prelude: Social Media Perspectives on Sora OpenAI and the Future of AI Video Generation](https://mlsanity.com/paper/2403.14665/) (2024)
- [The Impact of Generative AI on Social Media: An Experimental Study](https://mlsanity.com/paper/2506.14295/) (2025)
- [Characterizing AI-Generated Misinformation on Social Media](https://mlsanity.com/paper/2505.10266/) (2025)
- [Protect Your Prompts: Protocols for IP Protection in LLM Applications](https://mlsanity.com/paper/2306.06297/) (2023)
- ["Sora is Incredible and Scary": Emerging Governance Challenges of Text-to-Video Generative AI Models](https://mlsanity.com/paper/2406.11859/) (2024)
- [Examining the Impact of Label Detail and Content Stakes on User Perceptions of AI-Generated Images on Social Media](https://mlsanity.com/paper/2510.19024/) (2025)

## Abstract (arXiv)

As AI-generated video platforms rapidly advance, ethical challenges such as copyright infringement emerge. This study examines how users make sense of AI-generated videos on OpenAI's Sora by conducting a qualitative content analysis of user comments. Through a thematic analysis, we identified four dynamics that characterize how users negotiate authenticity, authorship, and platform governance on Sora. First, users acted as critical evaluators of realism, assessing micro-details such as lighting, shadows, fluid motion, and physics to judge whether AI-generated scenes could plausibly exist. Second, users increasingly shifted from passive viewers to active creators, expressing curiosity about prompts, techniques, and creative processes. Text prompts were perceived as intellectual property, generating concerns about plagiarism and remixing norms. Third, users reported blurred boundaries between real and synthetic media, worried about misinformation, and even questioned the authenticity of other commenters, suspecting bot-generated engagement. Fourth, users contested platform governance: some perceived moderation as inconsistent or opaque, while others shared tactics for evading prompt censorship through misspellings, alternative phrasing, emojis, or other languages. Despite this, many users also enforced ethical norms by discouraging the misuse of real people's images or disrespectful content. Together, these patterns highlighted how AI-mediated platforms complicate notions of reality, creativity, and rule-making in emerging digital ecosystems. Based on the findings, we discuss governance challenges in Sora and how user negotiations inform future platform governance.