What Do Humanities Scholars Need? A User Model for Recommendation in Digital Archives

TL;DR

This paper explores how humanities scholars' information-seeking behaviors in digital archives differ from typical recommender system assumptions, proposing a new user model based on qualitative research.

Contribution

It identifies four key dimensions of scholarly information-seeking that challenge standard RecSys user modeling assumptions and offers a diagnostic framework.

Findings

Preferences shift with research tasks and expertise

Relevance depends on verifiable provenance

Researchers seek items that challenge their current view

Abstract

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.