How to Evaluate Serendipity in Recommender Systems: the Need for a Serendiptionnaire

Abstract

Recommender systems can assist in various user tasks and serve diverse values, including exploring the item space. Serendipity has recently received considerable attention, often seen as a way to broaden users' tastes and counteract filter bubbles. However, the field of research on serendipity is fragmented regarding its evaluation methods, which impedes the progress of knowledge accumulation. This research plan proposes two studies to address these issues. First, a systematic literature review will be conducted to provide insights into how serendipity is currently studied in the field. This review will serve as a reference for novice researchers and help mitigate fragmentation by presenting a thorough overview of the field. This systematic literature review has already revealed a significant gap: the lack of a validated, widely accepted method for evaluating serendipity. Therefore, the second part of this research plan is to develop a validated questionnaire, the serendiptionnaire, to measure serendipity. This tool will provide a ground truth for evaluating serendipity, aiding in answering fundamental questions within the field and validating offline metrics.