人工智能与人类撰写回复的语言比较：在线心理健康查询
Linguistic Comparison of AI- and Human-Written Responses to Online Mental Health Queries
AI总结：
研究通过比较AI和人类回复的语义和语言特征，探讨AI在心理健康支持中的有效性及局限性。
摘要：
数字和在线技术的普及已改变了心理健康支持，网络心理健康社区（OMHCs）提供了安全的同伴支持空间。近年来，生成式AI和大型语言模型（LLMs）引入了可扩展的全天候心理健康援助，可能补充OMHCs的能力。尽管genAI在提供即时个性化回复方面有潜力，但其在复制人类同伴的细致、经验支持方面仍存疑问。本研究利用24,114条帖子和138,758条在线社区（OC）回复，从55个Reddit上的OMHCs中获取数据。我们 prompting 几种最先进的LLMs（GPT-4-Turbo、Llama-3和Mistral-7B）并基于心理语言学和词义学的多种语言措施，比较其回复与人类撰写（OC）回复。研究发现AI回复更冗长、易读且分析结构化，但缺乏人类互动中的语言多样性和个人叙述。通过定性分析，我们发现AI回复的中立立场及缺乏来回澄清的验证及补充见解。讨论了将生成式AI整合进OMHCs的伦理和实践影响，倡导平衡AI的可扩展性和及时性与人类连接不可替代的真实性、社会互动性和专业知识的框架。
英文摘要：
The ubiquity and widespread use of digital and online technologies have transformed mental health support, with online mental health communities (OMHCs) providing safe spaces for peer support. More recently, generative AI and large language models (LLMs) have introduced new possibilities for scalable, around-the-clock mental health assistance that could potentially augment and supplement the capabilities of OMHCs. Although genAI shows promise in delivering immediate and personalized responses, its effectiveness in replicating the nuanced, experience-based support of human peers remains an open question. In this study, we harnessed 24,114 posts and 138,758 online community (OC) responses from 55 OMHCs on Reddit. We prompted several state-of-the-art LLMs (GPT-4-Turbo, Llama-3, and Mistral-7B) with these posts, and compared their responses to human-written (OC) responses based on a variety of linguistic measures across psycholinguistics and lexico-semantics. Our findings revealed that AI responses are more verbose, readable, and analytically structured, but lack linguistic diversity and personal narratives inherent in human--human interactions. Through a qualitative examination, we found validation as well as complementary insights into the nature of AI responses, such as its neutral stance and the absence of seeking back-and-forth clarifications. We discuss the ethical and practical implications of integrating generative AI into OMHCs, advocating for frameworks that balance AI's scalability and timeliness with the irreplaceable authenticity, social interactiveness, and expertise of human connections that form the ethos of online support communities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
