Yuanhao Zhang

2papers

2 Papers

HCAug 1, 2024
DiscipLink: Unfolding Interdisciplinary Information Seeking Process via Human-AI Co-Exploration

Chengbo Zheng, Yuanhao Zhang, Zeyu Huang et al.

Interdisciplinary studies often require researchers to explore literature in diverse branches of knowledge. Yet, navigating through the highly scattered knowledge from unfamiliar disciplines poses a significant challenge. In this paper, we introduce DiscipLink, a novel interactive system that facilitates collaboration between researchers and large language models (LLMs) in interdisciplinary information seeking (IIS). Based on users' topics of interest, DiscipLink initiates exploratory questions from the perspectives of possible relevant fields of study, and users can further tailor these questions. DiscipLink then supports users in searching and screening papers under selected questions by automatically expanding queries with disciplinary-specific terminologies, extracting themes from retrieved papers, and highlighting the connections between papers and questions. Our evaluation, comprising a within-subject comparative experiment and an open-ended exploratory study, reveals that DiscipLink can effectively support researchers in breaking down disciplinary boundaries and integrating scattered knowledge in diverse fields. The findings underscore the potential of LLM-powered tools in fostering information-seeking practices and bolstering interdisciplinary research.

8.6HCApr 7
Designing AI-Infused Interactive Systems for Online Communities: A Systematic Literature Review

Yuanhao Zhang, Xiaoyu Wang, Jiaxiong Hu et al.

AI-infused systems have demonstrated remarkable capabilities in addressing diverse human needs within online communities. Their widespread adoption has shaped user experiences and community dynamics at scale. However, designing such systems requires a clear understanding of user needs, careful design decisions, and robust evaluation. While research on AI-infused systems for online communities has flourished in recent years, a comprehensive synthesis of this space remains absent. In this work, we present a systematic review of 77 studies, analyzing the systems they propose through three lenses: the challenges they aim to address, their design functionalities, and the evaluation strategies employed. The first two dimensions are organized around four core aspects of community participation: contribution, consumption, mediation, and moderation. Our analysis identifies common design and evaluation patterns, distills key design considerations, and highlights opportunities for future research on AI-infused systems in online communities.