What Do Humanities Scholars Need? A User Model for Recommendation in Digital Archives
For researchers designing recommender systems for scholarly digital archives, this paper provides a qualitative framework to address mismatches between standard user models and humanities scholars' needs.
This paper identifies four dimensions where humanities scholars' information-seeking behavior diverges from typical recommender system assumptions: context volatility, epistemic trust, contrastive seeking, and strand continuity. Based on focus groups and interviews with 18 researchers, it proposes a diagnostic framework for user modeling in digital archives.
User models for recommender systems (RecSys) typically assume stable preferences, similarity-based relevance, and session-bounded interactions -- assumptions derived from high-volume consumer contexts. This paper investigates these assumptions for humanities scholars working with digital archives. Following a human-centered design approach, we conducted focus groups and analyzed interview data from 18 researchers. Our analysis identifies four dimensions where scholarly information-seeking diverges from common RecSys user modeling: (1) context volatility -- preferences shift with research tasks and domain expertise; (2) epistemic trust -- relevance depends on verifiable provenance; (3) contrastive seeking -- researchers seek items that challenge their current direction; and (4) strand continuity -- research spans long-term threads rather than discrete sessions. We discuss implications for user modeling and outline how these dimensions relate to collaborative filtering, content-based, and session-based recommendation. We propose these dimensions as a diagnostic framework applicable beyond archives to similar application domains where typical user modeling assumptions may not hold.