对比AI与真人回复心理健康求助，发现AI更规范但缺乏情感共鸣。
Linguistic Comparison of AI- and Human-Written Responses to Online Mental Health Queries
- 用24,114条帖子和138,758条回复，比较AI与真人回复的语言特征。
- AI回复更长、更易读、结构更清晰，但缺少个人叙事和语言多样性。
- 适合关注AI在心理支持中应用边界的研究者与平台设计者。
数字技术的普及改变了心理健康支持方式，在线心理健康社区（OMHCs）为互助提供了安全空间。近年来，生成式AI与大语言模型（LLMs）为可扩展、全天候的心理支持带来了新可能，或可补充OMHCs能力。尽管生成式AI能提供即时个性化回应，但其是否能复现人类同伴所具有的细腻、基于经验的支持仍存疑问。本研究收集了来自Reddit上55个OMHCs的24,114条帖子及138,758条在线社区（OC）回复，使用GPT-4-Turbo、Llama-3和Mistral-7B等先进模型进行响应，并基于心理语言学与词法语义学多种指标，比较其与真人回复的差异。结果表明，AI回复更冗长、更易读、更具分析性结构，但缺乏人类互动中的语言多样性和个人叙述。定性分析进一步揭示，AI回复呈现中立立场，且不主动寻求澄清信息。我们讨论将生成式AI融入OMHCs的伦理与实践意义，倡导建立兼顾AI可扩展性与及时性，以及人类连接的真实性、社交互动性与专业性的平衡框架。
原文摘要 · Abstract (English)
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.
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