分析Reddit用户对ChatGPT和DeepSeek的评价，揭示公众对AI的信任与担忧。
Analyzing User Perceptions of Large Language Models (LLMs) on Reddit: Sentiment and Topic Modeling of ChatGPT and DeepSeek Discussions
- 通过情感分析与主题建模，挖掘用户讨论的核心议题。
- 识别出信任、偏见、伦理等五大关键话题，反映真实用户态度。
- 为开发者和政策制定者提供公众认知参考，适合关注AI社会影响的人群。
尽管关于ChatGPT和DeepSeek等大语言模型（LLMs）的网络讨论日益增多，但公众平台如Reddit上用户对这些模型的认知仍缺乏全面理解。这不容忽视，因为公众意见会影响AI的发展、信任度及未来政策。本研究利用情感分析与主题建模，分析Reddit上关于ChatGPT和DeepSeek的讨论，探索用户对人工智能的信任、期望、潜在用途、对模型偏见的顾虑以及伦理影响等核心议题。通过词频统计识别主流话题与情感趋势，并采用隐含狄利克雷分配（LDA）方法提取用户语言中的主要主题，包括LLM的潜在优势、技术应用及社会影响。研究旨在帮助开发者和政策制定者更清晰地理解公众如何认知和体验这些变革性技术，从而引导未来AI发展方向。
原文摘要 · Abstract (English)
While there is an increased discourse on large language models (LLMs) like ChatGPT and DeepSeek, there is no comprehensive understanding of how users of online platforms, like Reddit, perceive these models. This is an important omission because public opinion can influence AI development, trust, and future policy. This study aims at analyzing Reddit discussions about ChatGPT and DeepSeek using sentiment and topic modeling to advance the understanding of user attitudes. Some of the significant topics such as trust in AI, user expectations, potential uses of the tools, reservations about AI biases, and ethical implications of their use are explored in this study. By examining these concerns, the study provides a sense of how public sentiment might shape the direction of AI development going forward. The report also mentions whether users have faith in the technology and what they see as its future. A word frequency approach is used to identify broad topics and sentiment trends. Also, topic modeling through the Latent Dirichlet Allocation (LDA) method identifies top topics in users' language, for example, potential benefits of LLMs, their technological applications, and their overall social ramifications. The study aims to inform developers and policymakers by making it easier to see how users comprehend and experience these game-changing technologies.
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