分析五万五千条用户评论，揭示人机交互中的真实痛点。
A Lexical Analysis of online Reviews on Human-AI Interactions
- 通过词法分析55,968条在线评论，挖掘用户对AI的反馈
- 发现影响人机交互的关键因素，如信任与响应质量
- 适合关注AI用户体验和产品设计的研究者与开发者
本研究通过词法分析方法，考察55,968条来自G2.com、Producthunt.com和Trustpilot.com的在线用户评论，旨在理解人机交互中的复杂动态。尽管已有研究涉及用户感知与伦理问题，但对用户具体关切与挑战的认知仍不充分。初步因子分析揭示了影响交互体验的核心因素，后续内容分析将深入解析这些因素，以推动更以人为本的AI系统发展。研究结果有望深化对人机交互的理解，并为未来AI技术与用户体验优化提供依据。
原文摘要 · Abstract (English)
This study focuses on understanding the complex dynamics between humans and AI systems by analyzing user reviews. While previous research has explored various aspects of human-AI interaction, such as user perceptions and ethical considerations, there remains a gap in understanding the specific concerns and challenges users face. By using a lexical approach to analyze 55,968 online reviews from G2.com, Producthunt.com, and Trustpilot.com, this preliminary research aims to analyze human-AI interaction. Initial results from factor analysis reveal key factors influencing these interactions. The study aims to provide deeper insights into these factors through content analysis, contributing to the development of more user-centric AI systems. The findings are expected to enhance our understanding of human-AI interaction and inform future AI technology and user experience improvements.
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