What Is Serendipity? An Interview Study to Conceptualize Experienced Serendipity in Recommender Systems

TL;DR

This study tackles the ambiguity of serendipity in recommender systems by eliciting users’ subjective experiences through 17 interviews and analyzing them with grounded theory. The authors conceptualize experienced serendipity as a three-component construct—fortuitous, refreshing, and enriching—that is necessary and sufficient for a serendipitous experience, and show how these components can be realized via multiple condition combinations to yield distinct flavors. The resulting framework unifies prior definitions, clarifies the relationship between relevance, novelty, and unexpectedness, and reveals underexplored flavors such as taste-broadening and taste-deepening serendipity. Practically, the framework provides guidance for consistent operationalization and informs RecSys design practices aimed at stimulating serendipity while highlighting potential edge cases and negative experiences.

Abstract

Serendipity has been associated with numerous benefits in the context of recommender systems, e.g., increased user satisfaction and consumption of long-tail items. Despite this, serendipity in the context of recommender systems has thus far remained conceptually ambiguous. This conceptual ambiguity has led to inconsistent operationalizations between studies, making it difficult to compare and synthesize findings. In this paper, we conceptualize the user's experience of serendipity. To this effect, we interviewed 17 participants and analyzed the data following the grounded theory paradigm. Based on these interviews, we conceptualize experienced serendipity as "a user experience in which a user unintentionally encounters content that feels fortuitous, refreshing, and enriching". We find that all three components -- fortuitous, refreshing and enriching -- are necessary and together are sufficient to classify a user's experience as serendipitous. However, these components can be satisfied through a variety of conditions. Our conceptualization unifies previous definitions of serendipity within a single framework, resolving inconsistencies by identifying distinct flavors of serendipity. It highlights underexposed flavors, offering new insights into how users experience serendipity in the context of recommender systems. By clarifying the components and conditions of experienced serendipity in recommender systems, this work can guide the design of recommender systems that stimulate experienced serendipity in their users, and lays the groundwork for developing a standardized operationalization of experienced serendipity in its many flavors, enabling more consistent and comparable evaluations.