Sora OpenAI's Prelude: Social Media Perspectives on Sora OpenAI and the Future of AI Video Generation
Not on the map. Why?
Abstract (arXiv)
The rapid advancement of Generative AI (Gen-AI) is transforming Human-Computer Interaction (HCI), with significant implications across various sectors. This study investigates the public's perception of Sora OpenAI, a pioneering Gen-AI video generation tool, via social media discussions on Reddit before its release. It centers on two main questions: the envisioned applications and the concerns related to Sora's integration. The analysis forecasts positive shifts in content creation, predicting that Sora will democratize video marketing and innovate game development by making video production more accessible and economical. Conversely, there are concerns about deepfakes and the potential for disinformation, underscoring the need for strategies to address disinformation and bias. This paper contributes to the Gen-AI discourse by fostering discussion on current and future capabilities, enriching the understanding of public expectations, and establishing a temporal benchmark for user anticipation. This research underscores the necessity for informed, ethical approaches to AI development and integration, ensuring that technological advancements align with societal values and user needs.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Mar 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 4; 2025: 2; 2026: 2.
8 papers.
- 2024The Dawn of Video Generation: Preliminary Explorations with SORA-like Modelscited by 30
- 2024Bora: Biomedical Generalist Video Generation Modelcited by 15
- 2024The Great AI Witch Hunt: Reviewers Perception and (Mis)Conception of Generative AI in Research Writingcited by 6
- 2024"Sora is Incredible and Scary": Emerging Governance Challenges of Text-to-Video Generative AI Modelscited by 3
- 2026Generative AI for Video Trailer Synthesis: From Extractive Heuristics to Autoregressive Creativitycited by 2
- 2026SKeDA: A Generative Watermarking Framework for Text-to-video Diffusion Modelscited by 1
- 2025Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidentscited by 0
- 2025User Negotiations of Authenticity, Ownership, and Governance on AI-Generated Video Platforms: Evidence from Soracited by 0
- 2026Generative AI for Video Trailer Synthesis: From Extractive Heuristics to Autoregressive Creativity3 Apr 2026
- 2026SKeDA: A Generative Watermarking Framework for Text-to-video Diffusion Models27 Feb 2026
- 2025User Negotiations of Authenticity, Ownership, and Governance on AI-Generated Video Platforms: Evidence from Sora5 Dec 2025
- 2025Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents28 Mar 2025
- 2024The Dawn of Video Generation: Preliminary Explorations with SORA-like Models7 Oct 2024
- 2024Bora: Biomedical Generalist Video Generation Model12 Jul 2024
- 2024The Great AI Witch Hunt: Reviewers Perception and (Mis)Conception of Generative AI in Research Writing27 Jun 2024
- 2024"Sora is Incredible and Scary": Emerging Governance Challenges of Text-to-Video Generative AI Models10 Apr 2024