SoulSeek: Exploring the Use of Social Cues in LLM-based Information Seeking
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 13 of its 65 references that are in the map. First posted on arXiv 3 Jan 2026.
Builds on
13 of 65 references.
References · 13
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- 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
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Citing papers per year: 2026: 1.
1 paper.
- 2026SocialBuddy: Tailoring Search Agent for Social Scenarioscited by 0
- 2026SocialBuddy: Tailoring Search Agent for Social Scenarios28 Aug 2026