32 citations · 84 across the 14 of their papers we have counts for
14 papers
Correct Yourself, Keep My Trust: How Self-Correction and Social Connection Shape Credibility in Social Chatbots
Biswadeep Sen, Yi-Chieh Lee
When social chatbots make mistakes, and they do, how they recover determines whether users trust them again. Social chatbots are increasingly integrated into everyday life, yet the…
Understanding and Supporting Online Discussion with Opinionated Chatbots
Tianqi Song, Chi-Lan Yang, Zihan Liu +3
Opinionated chatbots are increasingly present on online platforms and have the potential to shape public discourse by influencing individuals' viewpoints before they engage in disc…
ConvScale: Conversational Interviews for Scale-Aligned Measurement
Peinuan Qin, Jingzhu Chen, Yitian Yang +3
Conversational interviews are commonly used to complement structured surveys by eliciting rich and contextualized responses, which are typically analyzed qualitatively. However, th…
Fit Matters: Format-Distance Alignment Improves Conversational Search
Yitian Yang, Yugin Tan, Jung-Tai King +2
Existing conversational search systems can synthesize information into responses, but they lack principled ways to adapt response formats to users' cognitive states. This paper inv…
AI-exhibited Personality Traits Can Shape Human Self-concept through Conversations
Jingshu Li, Tianqi Song, Nattapat Boonprakong +3
Recent Large Language Model (LLM) based AI can exhibit recognizable and measurable personality traits during conversations to improve user experience. However, as human understandi…
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…
Timing Matters: How Using LLMs at Different Timings Influences Writers' Perceptions and Ideation Outcomes in AI-Assisted Ideation
Peinuan Qin, Chi-Lan Yang, Jingshu Li +2
Large Language Models (LLMs) have been widely used to support ideation in the writing process. However, whether generating ideas with the help of LLMs leads to idea fixation or ide…
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…
Mining Evidence about Your Symptoms: Mitigating Availability Bias in Online Self-Diagnosis
Junti Zhang, Zicheng Zhu, Jingshu Li +1
People frequently exposed to health information on social media tend to overestimate their symptoms during online self-diagnosis due to availability bias. This may lead to incorrec…
As Confidence Aligns: Exploring the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Making
Jingshu Li, Yitian Yang, Q. Vera Liao +2
Complementary collaboration between humans and AI is essential for human-AI decision making. One feasible approach to achieving it involves accounting for the calibrated confidence…
Wild Narratives: Exploring the Effects of Animal Chatbots on Empathy and Positive Attitudes toward Animals
Jingshu Li, Aaditya Patwari, Yi-Chieh Lee
Rises in the number of animal abuse cases are reported around the world. While chatbots have been effective in influencing their users' perceptions and behaviors, little if any res…
Understanding How Psychological Distance Influences User Preferences in Conversational Versus Web Search
Yitian Yang, Yugin Tan, Yang Chen Lin +3
Conversational search offers an easier and faster alternative to conventional web search, while having downsides like lack of source verification. Research has examined performance…
Exploring the Human-LLM Synergy in Advancing Theory-driven Qualitative Analysis
Han Meng, Yitian Yang, Wayne Fu +3
Qualitative coding is a demanding yet crucial research method in the field of Human-Computer Interaction (HCI). While recent studies have shown the capability of large language mod…
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…