The Rise of AI Companions: How Human-Chatbot Relationships Influence Well-Being

聊天机器人 社会关系 心理学 社会心理学 社交网络(社会语言学) 互联网隐私 社会关系 人际关系 虚拟世界 人际互动 计算机科学 人类行为 人际关系 万维网 社会支持 互联网
作者
Yutong Zhang,Dora Zhao,Jeffrey T. Hancock,Robert E. Kraut,Diyi Yang
标识
DOI:10.48550/arxiv.2506.12605
摘要

As large language models (LLMs)-enhanced chatbots grow increasingly expressive and socially responsive, many users are beginning to form companionship-like bonds with them, particularly with simulated AI partners designed to mimic emotionally attuned interlocutors. These emerging AI companions raise critical questions: Can such systems fulfill social needs typically met by human relationships? How do they shape psychological well-being? And what new risks arise as users develop emotional ties to non-human agents? This study investigates how people interact with AI companions, especially simulated partners on CharacterAI, and how this use is associated with users' psychological well-being. We analyzed survey data from 1,131 users and 4,363 chat sessions (413,509 messages) donated by 244 participants, focusing on three dimensions of use: nature of the interaction, interaction intensity, and self-disclosure. By triangulating self-reports primary motivation, open-ended relationship descriptions, and annotated chat transcripts, we identify patterns in how users engage with AI companions and its associations with well-being. Findings suggest that people with smaller social networks are more likely to turn to chatbots for companionship, but that companionship-oriented chatbot usage is consistently associated with lower well-being, particularly when people use the chatbots more intensively, engage in higher levels of self-disclosure, and lack strong human social support. Even though some people turn to chatbots to fulfill social needs, these uses of chatbots do not fully substitute for human connection. As a result, the psychological benefits may be limited, and the relationship could pose risks for more socially isolated or emotionally vulnerable users.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
shisong发布了新的文献求助10
刚刚
刚刚
活泼的雨真完成签到,获得积分10
刚刚
orixero应助犹豫的若采纳,获得10
1秒前
ccc发布了新的文献求助10
1秒前
1秒前
六六关注了科研通微信公众号
1秒前
科研通AI6.2应助kk采纳,获得80
2秒前
搞怪的冬灵完成签到,获得积分10
2秒前
科研通AI2S应助科研通管家采纳,获得10
2秒前
DW应助科研通管家采纳,获得10
2秒前
dde应助科研通管家采纳,获得10
2秒前
2秒前
2秒前
隐形曼青应助科研通管家采纳,获得20
2秒前
JamesPei应助科研通管家采纳,获得10
3秒前
领导范儿应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
沉默诗柳完成签到,获得积分10
4秒前
4秒前
巴拉巴拉发布了新的文献求助10
4秒前
4秒前
英俊的铭应助科研通管家采纳,获得10
4秒前
Terry发布了新的文献求助10
4秒前
4秒前
英姑应助科研通管家采纳,获得10
4秒前
muttcy完成签到,获得积分10
4秒前
传奇3应助科研通管家采纳,获得10
4秒前
61完成签到,获得积分10
4秒前
汉堡包应助科研通管家采纳,获得10
4秒前
小马甲应助科研通管家采纳,获得10
4秒前
4秒前
酷波er应助科研通管家采纳,获得10
5秒前
5秒前
图图发布了新的文献求助20
5秒前
Leanne完成签到,获得积分10
5秒前
传奇3应助科研通管家采纳,获得10
5秒前
5秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
DIPPR Project 801 - Full Version 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7767307
求助须知:如何正确求助?哪些是违规求助? 9310984
关于积分的说明 20320681
捐赠科研通 7352278
什么是DOI,文献DOI怎么找? 3315268
关于科研通互助平台的介绍 2464651
邀请新用户注册赠送积分活动 2329934