数字时代寻求帮助：对技术辅助虐待受害者在线支持系统的跨平台分析

中文摘要 AI 辅助

技术辅助虐待（TFA）利用数字技术跟踪、骚扰、监视或威胁他人，已成为一种普遍的人际伤害形式。受害者向在线资源寻求指导，其回应会影响受害者对风险的评估、对虐待的解读及保护行动的选择。本文对TFA受害者在网络搜索、同伴支持论坛和对话式人工智能系统这三个渠道的在线支持进行大规模评估。利用来自r/Stalking的十年受害者叙述，通过定性编码和监督分类器构建了一个涵盖11类技术滥用的TFA查询数据集。在三个渠道模拟这些查询，并使用一个统一框架评估回应，该框架涵盖技术、社会和安全维度，包括相关性、准确性、可操作性、说服力、可理解性以及平台风险和支持特征等。通过构建和验证自动分类器来扩大评估规模。研究发现各平台支持质量存在差异。谷歌搜索和通用语言模型提供的指导比Reddit讨论更相关且可操作，但都不能始终提供安全、考虑创伤的支持。超过65%的受害者查询在搜索结果中遇到潜在恶意链接，超过20%的Reddit讨论包含有害回应，对话式人工智能系统经常无法提供有风险意识的指导或具体支持资源。令人惊讶的是，特定领域的幸存者支持聊天机器人在大多数维度上表现不如通用语言模型。这些发现揭示了TFA受害者数字支持的弱点，强调了未来支持技术以安全为中心设计、评估和部署的必要性。

英文摘要

Technology-facilitated abuse (TFA) creates an adversarial setting where sound cybersecurity advice can be unsafe: changing credentials or resetting devices may alert an abuser, destroy evidence, or increase escalation risk. Victims seek guidance from search engines, peer forums, and conversational AI, often evaluated for relevance and correctness rather than contextual safety. We measure whether these sources meet victims' needs. From a decade of r/Stalking narratives, we construct 2,797 victim-derived queries spanning 11 misuse categories. We analyze 27,162 Google webpages, 2,476 Reddit query--thread responses, and 250 responses from three general-purpose LLMs and two survivor-support chatbots. Our framework measures technical quality and damaging guidance, plus secondary-link integrity on webpages, toxicity on Reddit, and trauma-informed support in conversational systems. We find failures & risks that relevance, accuracy, or actionability alone do not capture. Web Search and conversational systems frequently return relevant information; Reddit responses are less consistently relevant and actionable. In our evaluated accuracy sample, 17.3% of webpages, 13.3% of Reddit threads, and 19.6% of conversational AI responses contained damaging guidance. Further, 65.5% of victim queries led to a webpage with a secondary URL flagged by multiple VirusTotal engines, over 20% received a toxic Reddit comment, and every conversational system produced guidance that overlooked escalation risk. Specialization did not guarantee better support: HopeChat underperformed general-purpose LLMs on several dimensions, while Ruth remained limited in trauma-informed support. These findings expose a gap between technical quality and contextual safety. Safe TFA assistance requires risk-aware recommendations, trustworthy sources, uncertainty communication, and human support, beyond technically plausible answers.

发表机构

• Northeastern University（东北大学）
• The University of Texas at Arlington（阿灵顿德州大学）

机构由 AI 辅助整理，请以论文原文为准。