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2026-01-03 07:09 UTC · cs.HC · cs.HC, cs.AI, cs.IR

SoulSeek: Exploring the Use of Social Cues in LLM-based Information Seeking

Yubo Shu, Peng Zhang, Meng Wu, Yan Chen, Haoxuan Zhou, Guanming Liu, Yu Zhang, Liuxin Zhang, Qianying Wang, Tun Lu, Ning Gu

Social cues, which convey others' presence, behaviors, or identities, play a crucial role in human information seeking by helping individuals judge relevance and trustworthiness. However, existing LLM-based search systems primarily rely on semantic features, creating a misalignment with the socialized cognition underlying natural information seeking. To address this gap, we explore how the integration of social cues into LLM-based search influences users' perceptions, experiences, and behaviors. Focusing on social media platforms that are beginning to adopt LLM-based search, we integrate design workshops, the implementation of the prototype system (SoulSeek), a between-subjects study, and mixed-method analyses to examine both outcome- and process-level findings. The workshop informs the prototype's cue-integrated design. The study shows that social cues improve perceived outcomes and experiences, promote reflective information behaviors, and reveal limits of current LLM-based search. We propose design implications emphasizing better social-knowledge understanding, personalized cue settings, and controllable interactions.
arXiv abstractPDF

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