Online Music Listening Culture of Kids and Adolescents: Listening Analysis and Music Recommendation Tailored to the Young
In this paper, we analyze a large dataset of user-generated music listening events from Last.fm, focusing on users aged 6 to 18 years. Our contribution is two-fold. First, we study the music genre preferences of this young user group and analyze these preferences for homogeneity within more fine-grained age groups and with respect to gender and countries. Second, we investigate the performance of a collaborative filtering recommender when tailoring music recommendations to different age groups. We find that doing so improves performance for all user groups up to 18 years, but decreases performance for adult users aged 19 years and older.
Code (0)
등록된 구현이 없습니다.
Tasks
Collaborative FilteringCultural Vocal Bursts Intensity PredictionMusic RecommendationSimilar Papers 제목 키워드 기반
Predicting Musical Sophistication from Music Listening Behaviors: A Preliminary Study
Psychological models are increasingly being used to explain online behavioral traces. Aside from the commonly used personality traits as a general user model, more domain dependent models are gaining attention. The use o…
Decoding Selective Auditory Attention to Musical Elements in Ecologically Valid Music Listening
Art has long played a profound role in shaping human emotion, cognition, and behavior. While visual arts such as painting and architecture have been studied through eye tracking, revealing distinct gaze patterns between …
Static and Dynamic Measures of Active Music Listening as Indicators of Depression Risk
Music, an integral part of our lives, which is not only a source of entertainment but plays an important role in mental well-being by impacting moods, emotions and other affective states. Music preferences and listening …
Taste or Addiction?: Using Play Logs to Infer Song Selection Motivation
Online music services are increasing in popularity. They enable us to analyze people's music listening behavior based on play logs. Although it is known that people listen to music based on topic (e.g., rock or jazz), we…
Tag2Risk: Harnessing Social Music Tags for Characterizing Depression Risk
Musical preferences have been considered a mirror of the self. In this age of Big Data, online music streaming services allow us to capture ecologically valid music listening behavior and provide a rich source of informa…
valid