Does the User Have A Theory of the Recommender? A Grounded Theory Study.

User Modeling, Adaptation, and Personalization (UMAP)(2022)

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摘要
Recommender systems have gained widespread adoption in many web applications. Modern internet users experience daily interactions with recommender systems. Consequently, users, through these interactive experiences, have developed an inherent understanding of how recommender systems work, what their objectives are, and how the user might manipulate them. We describe this understanding as the Theory of the Recommender. In this paper, we explore the users’ perception and understanding of the recommender system in an empirical study using a grounded theory methodology. To that end, we draw on the cognitive theory of mind to propose a comprehensive theoretical framework that explains the users’ interpretation of the recommender system’s knowledge, reasoning, motivation, beliefs and attitudes. Our findings, based on individual in-depth interviews, suggest that users possess a sophisticated understanding of the recommender system’s behavior. Identifying the user’s understanding is a necessary step in evaluating their impact and improving recommender systems accordingly. Finally, we discuss the potential implications of such user knowledge on recommendation performance.
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