Spotify Warped: Reshaping Personal Informatics via Music Listening, Casual Users, Passive Data and Episodic Reflection

Paper Title

Spotify Warped: Reshaping Personal Informatics via Music Listening, Casual Users, Passive Data and Episodic Reflection

Publication Info

• Topic area: Personal informatics with a focus on casual users, passive data, and episodic reflection in music listening.
• Keywords: Personal informatics, casual users, passive data, episodic reflection, music listening, Spotify Wrapped, self-tracking, quantified self, data engagement, user insights.

Background and Problem

• Problem / challenge: Existing personal informatics frameworks focus on active, intentional self-tracking by Quantified Self (QS) users, neglecting casual users (CUs) who engage episodically with passively collected data. Current summaries, like Spotify Wrapped, offer limited exploration and fail to meet diverse user needs.
• Significance: Understanding casual users’ interactions with passively collected data can broaden personal informatics research and improve the design of data summaries to better serve a growing audience of non-tracking users.
• Motivation and related work: Prior work has focused on QS users’ active tracking and reflection, emphasizing goal-oriented domains like health and fitness. Casual users, who rely on provider-curated summaries, remain underexplored. Music listening, with its passively collected data and popular summaries like Spotify Wrapped, provides an ideal lens to study these gaps.

Solution

• Proposed approach: The paper investigates casual users’ data interests and abstract insights in the music listening domain, contrasts these with existing summaries, and proposes an information space framework to describe user needs. It also offers a provocation to update personal informatics models for casual users and passive data.
• Novelty:
  1. Empirical insights into casual users’ and self-trackers’ (STs) data interests and abstract insights in music listening.
  2. Identification of gaps between user needs and existing music summaries.
  3. Introduction of an information space framework for describing user insights, generalizable across domains.
  4. A provocation to augment personal informatics frameworks to include casual users, passive data, and episodic reflection.
• Procedure and key techniques:
  • Conducted an online survey with 60 participants to explore data interests and abstract insights.
  • Analyzed responses using quantitative (Likert scales, t-tests) and qualitative (thematic coding) methods.
  • Compared casual users and self-trackers to identify differences in data engagement.
  • Evaluated the capabilities of existing music summaries and barriers to accessing full listening histories.

Results

• Concrete findings:
  • Users are most interested in artist- and track-related data, with genre being the most popular attribute across all categories.
  • Casual users and self-trackers share similar abstract insights but differ in their understanding of relevant data fields.
  • 82% of users were unaware they could access their full listening history, and 42% expressed interest in exploring it.
  • Existing summaries partially satisfy user needs but lack granularity, temporal insights, and support for exploration.
• Advantage over baselines:
  • Highlights the insufficiency of current personal informatics frameworks and music summaries in addressing casual users’ curiosity and data needs.
  • Proposes a novel information space framework to bridge the gap between data and insights for casual users.
• Experiments / evaluation:
  • Surveyed 60 U.S.-based participants (28 men, 30 women, 2 nonbinary; mean age 35.33) using Prolific.
  • Collected 236 insights and analyzed them to identify themes and subthemes of user interests.
  • Evaluated existing summaries from Spotify, Apple Music, Tencent, Amazon, and YouTube Music.
• Limitations and future work:
  • Limited to U.S.-based participants, potentially reducing generalizability.
  • Insights elicited may be non-exhaustive due to survey design.
  • Future work should explore these themes on a larger scale, include more diverse populations, and investigate the unique position of music listening within personal informatics.

Summary

This paper investigates how casual users engage with passively collected music listening data, contrasting their data interests and abstract insights with existing summaries like Spotify Wrapped. It introduces an information space framework to describe user needs and highlights gaps in current personal informatics models, which focus on active self-tracking. The findings reveal that casual users are curious about their data but face barriers to exploration due to limited summaries and conceptual disconnects. The paper proposes augmenting personal informatics frameworks to better account for casual users, passive data, and episodic reflection, with implications for other domains like fitness and screen-time tracking.