Shuoqi investigates how contemporary search interfaces, such as web search engines, generative assistants, and social platforms, interact with user diversity to shape search behavior and query formulation. While information retrieval (IR) systems evolve rapidly, theories of human information seeking have lagged, risking misaligned designs and unclear effects on cognition, effort, trust, and satisfaction. Shuoqi first develops a comprehensive, human-centered framework that captures today’s information-seeking process across systems, user traits, and contexts, specifying core constructs and variables (Sun et al., 2025). Building on this scaffold, he examines how interface preferences vary with information needs (e.g., known-item vs. exploratory), situational constraints (e.g., time pressure), and perceived stakes (e.g., financial consequences). He then quantifies how using preferred versus non-preferred interfaces and interfaces with differing affordances affects observable behavior (query formulation, time on task, etc.) and cognitive state (confidence, perceived effort, trust) before and after search. Finally, he integrates these findings into a behavioral model that predicts interface preference and user behavior across contexts. Methodologically, his work combines controlled experiments, large-scale log analyses, and surveys to triangulate mechanisms and external validity. Contributions include: (1) a modern framework for studying information seeking with diverse users and interfaces; (2) empirical characterizations linking needs, contexts, and interface attributes to behavior and cognition; and (3) a predictive model of interface choice and user behavior. The results inform IR evaluation beyond relevance-only metrics, guiding design and personalization toward trustworthy, inclusive, and effective search, laying the groundwork for adaptive, agentic IR ecosystems.
Shuoqi is a scholarship recipient of the ARC Centre for Automated Decision-Making and Society (ADM+S) and is supervised by Dr. Danula Hettiachchi and Dr. Damiano Spina. Visit Shuoqi’s personal website learn more about his research.
References
SIGIR-AP
ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments
Shuoqi Sun, Danula Hettiachchi, and Damiano Spina
In Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region (SIGIR-AP ’25), 2025
The modern information environment (MIE) is increasingly complex, shaped by a wide range of techniques designed to satisfy users’ information needs. Information seeking (IS) models are effective mechanisms for characterizing user-system interactions. However, conceptualizing a model that fully captures the MIE landscape poses a challenge. We argue: Does such a model exist? To address this, we propose the Information Seeking in Modern Information Environments (ISMIE) framework as a fundamental step. ISMIE conceptualizes the information seeking process (ISP) via three key concepts: Components (e.g., Information Seeker), Intervening Variables (e.g., Interactive Variables), and Activities (e.g., Acquiring). Using ISMIE’s concepts and employing a case study based on a common scenario - misinformation dissemination – we analyze six existing IS and information retrieval (IR) models to illustrate their limitations and the necessity of ISMIE. We then show how ISMIE serves as an actionable framework for both characterization and experimental design. We characterize three pressing issues and then outline two research blueprints: a user-centric, industry-driven experimental design for the authenticity and trust crisis to AI-generated content and a system-oriented, academic-driven design for tackling dopamine-driven content consumption. Our framework offers a foundation for developing IS and IR models to advance knowledge on understanding human interactions and system design in MIEs.
@inproceedings{Sun2025-ia,title={ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments},author={Sun, Shuoqi and Hettiachchi, Danula and Spina, Damiano},booktitle={Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region},year={2025},series={SIGIR-AP '25},doi={10.1145/3767695.3769509},publisher={ACM},pages={385–395},}
