调研用户对恋爱平台中AI聊天伙伴的接受度，发现主动用和被动遇的反应差异显著。
Two-sided receptivity to conversational AI agents in online dating: Bilingual survey data from Fledge.Love
- 区分主动使用AI和被动接触他人用的AI，分别测量接受度
- 近八成用户愿意用AI作为聊天助手，但对陌生人的AI身份接受度低
- 数据开源支持跨文化人机交互研究，适合关注AI社交应用的学者
自主对话代理与生成式AI功能正快速被引入在线约会平台，但公众对其用户态度的实证证据仍不足，尤其缺乏对“接收端”反应的研究：人们如何回应机器生成的资料、信息或聊天对象？本文发布两个匿名调查数据集，来自国际用户群体的Fledge.Love平台。第一个数据集（N = 2,617；俄语和英语版本）通过七项量表评估用户对自主对话代理的接受度，明确区分“自己使用代理”与“遇到别人用的代理”两种角色，并包含六个有序协变量和两项辅助问题。第二个数据集（N = 2,894）衡量用户对三种被动生成式AI功能的兴趣。数据集包含2,499个完整案例的模型推导得分，附有双语代码本、经过k-匿名性审计的匿名化流程文档、可执行分析笔记本及标准输出结果，支持在人机通信、推荐系统与跨文化技术接受度研究中的复用。
原文摘要 · Abstract (English)
Autonomous conversational agents and generative-AI features are being added to online dating platforms faster than public evidence about user attitudes can accumulate, and the scarcest evidence concerns the receiving side: how people react when the profiles, messages, or conversation partners they encounter are machine-generated. We release two anonymized survey datasets collected from active users of Fledge.Love, a dating platform serving an international user base. The first (N = 2,617; Russian and English forms) measures receptivity to autonomous conversational agents with a seven-item battery that separates the principal role (deploying one's own agent) from the counterpart role (encountering someone else's), plus six ordinal covariates and two auxiliary items. The second (N = 2,894) measures interest in three passive generative-AI features. The release includes model-derived scores for 2,499 complete cases, a bilingual codebook, a documented anonymization pipeline with a k-anonymity audit, executable analysis notebooks, and canonical outputs, supporting reuse in human-AI communication, recommender-systems, and cross-cultural technology-acceptance research.
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