Understanding user perceptions of DeepSeek: insights from sentiment, topic and network analysis using a Reddit-based...

Area of Science:

• Artificial Intelligence
• Computational Social Science
• Sociotechnical Systems

Background:

• The launch of DeepSeek, a Chinese open-source generative AI model, prompted significant public discussion.
• The r/deepseek subreddit served as a primary platform for evaluating the AI model's capabilities and societal implications.

Purpose of the Study:

• To analyze the sociotechnical perceptions surrounding DeepSeek by examining online discourse.
• To understand public sentiment, emotions, and key themes related to the integration of emerging AI systems.

Main Methods:

• Analysis of 46,649 posts and comments from r/deepseek (January-May 2025).
• Utilized VADER sentiment analysis, Hartmann emotion classification, BERTopic modeling, hyperlink extraction, and network analysis.
• Correlated sentiment/emotion scores with dominant topics and community engagement patterns.

Main Results:

• Predominantly positive sentiment (47.23% posts, 44.26% comments), with neutrality, surprise, and fear as key emotions.
• Top topics included open-source AI, DeepSeek usage, device compatibility, ChatGPT comparisons, and censorship concerns.
• Hyperlinks pointed to GitHub, Hugging Face, and DeepSeek services; network analysis identified 'Open-Source AI Models' as a cohesive cluster.

Conclusions:

• Community perception framed DeepSeek as both a technical tool and a geopolitical entity.
• Enthusiasm for DeepSeek's performance and open-source nature contrasted with concerns about censorship, privacy, and ideological influence.
• Collective perception evolved through decentralized dialogue, reflecting broader tensions in global AI development regarding openness, trust, and legitimacy.