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20242026
most citedThe Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships

111 citations · 152 across the 14 of their papers we have counts for

collaborators

17 papers

cs.HC2026

Stereotypically Yours: Portrayal and Perception of Race-Coded AI Companions

Wang Claire, Jiayue Melissa Shi, Agam Goyal +4

AI companions can purportedly adopt racial personas, raising questions about how they represent identity and how users interpret these portrayals. We combined an algorithmic audit…

cs.HC2026

Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions

Chau Do, Yunhao Yuan, Koustuv Saha +2

AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion disruptions: platform changes tha…

cs.HC2026

When AI Companions Disappear: Relational Continuity and Collective Contestation during China's National AI Regulatory Transition

Yunhao Yuan, Kejia Zhang, Yuqi Niu +3

AI model updates and service withdrawals can disrupt relationships with AI companions, but research has largely examined individual platform events. Less is known about users' resp…

cs.CY2026

CompanionHarm: A Multi-Turn Benchmark for Detecting Harms in Real-World AI Companion Conversations

Renwen Zhang, Han Meng, Jian Chai +2

As AI companions become increasingly embedded in everyday life, there is an urgent need to detect harms that emerge in social and emotional human-AI interactions. Yet research in t…

cs.CY2026

Reshaping Undergraduate Computer Science Education in the Generative AI Era

Yi-Chieh Lee, Nattapat Boonprakong, Yugin Tan +20

Generative AI represents a turning point for Computer Science (CS) education. In recent decades, post-secondary CS education has largely focused on what has been seen as practical…

cs.HC2026

Push and Pushback in Contesting AI: Demands for and Resistance to Accountability

Yulu Pi, Lucas Lichner, Jae Woo Lee +3

As AI becomes increasingly embedded in daily life, it has been shown to fail critically, cause harm, and spark public controversy, prompting affected communities, workers, and publ…

cs.HC2026

The Fragility of AI Companionship: Ontological, Structural, and Normative Uncertainty in Human-AI Relationships

Renwen Zhang, Lezi Xie

As generative AI chatbots become more personalized and emotionally responsive, they increasingly serve as companions, friends, and romantic partners. Yet these relationships are ac…

cs.HC2026

Designing Computational Tools for Exploring Causal Relationships in Qualitative Data

Han Meng, Qiuyuan Lyu, Peinuan Qin +4

Exploring causal relationships for qualitative data analysis in HCI and social science research enables the understanding of user needs and theory building. However, current comput…

cs.HC2025★ 5 cited

Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Theory

Yunhao Yuan, Jiaxun Zhang, Talayeh Aledavood +2

AI-powered companion chatbots (AICCs) such as Replika are increasingly popular, offering empathetic interactions, yet their psychosocial impacts remain unclear. We examined how eng…

cs.HC2025★ 9 cited

Exploring the Effects of Chatbot Anthropomorphism and Human Empathy on Human Prosocial Behavior Toward Chatbots

Jingshu Li, Zicheng Zhu, Renwen Zhang +1

Chatbots are increasingly integrated into people's lives and are widely used to help people. Recently, there has also been growing interest in the reverse direction-humans help cha…

cs.CL2025

What is Stigma Attributed to? A Theory-Grounded, Expert-Annotated Interview Corpus for Demystifying Mental-Health Stigma

Han Meng, Yancan Chen, Yunan Li +4

Mental-health stigma remains a pervasive social problem that hampers treatment-seeking and recovery. Existing resources for training neural models to finely classify such stigma ar…

cs.HC2025★ 4 cited

Empowering Social Service with AI: Insights from a Participatory Design Study with Practitioners

Yugin Tan, Kai Xin Soh, Renwen Zhang +4

In social service, administrative burdens and decision-making challenges often hinder practitioners from performing effective casework. Generative AI (GenAI) offers significant pot…

cs.AI2025★ 8 cited

Relational Norms for Human-AI Cooperation

Brian D. Earp, Sebastian Porsdam Mann, Mateo Aboy +59

How we should design and interact with social artificial intelligence depends on the socio-relational role the AI is meant to emulate or occupy. In human society, relationships suc…

cs.HC2025

Deconstructing Depression Stigma: Integrating AI-driven Data Collection and Analysis with Causal Knowledge Graphs

Han Meng, Renwen Zhang, Ganyi Wang +4

Mental-illness stigma is a persistent social problem, hampering both treatment-seeking and recovery. Accordingly, there is a pressing need to understand it more clearly, but analyz…

cs.HC2025★ 1 cited

The Benefits of Prosociality towards AI Agents: Examining the Effects of Helping AI Agents on Human Well-Being

Zicheng Zhu, Yugin Tan, Naomi Yamashita +2

Prosocial behaviors, such as helping others, are well-known to enhance human well-being. While there is a growing trend of humans helping AI agents, it remains unclear whether the…

cs.HC2024★ 111 cited

The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships

Renwen Zhang, Han Li, Han Meng +3

As conversational AI systems increasingly permeate the socio-emotional realms of human life, they bring both benefits and risks to individuals and society. Despite extensive resear…

cs.AI2024★ 14 cited

Understanding the Effects of Miscalibrated AI Confidence on User Trust, Reliance, and Decision Efficacy

Jingshu Li, Yitian Yang, Renwen Zhang +4

Providing well-calibrated AI confidence can help promote users' appropriate trust in and reliance on AI, which are essential for AI-assisted decision-making. However, calibrating A…