The Melancholic Muse: Analyzing Listeners' Emotional Resonance with Sad Music

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

This study examines how listeners' emotional perspectives are influenced by the tone, lyrics, and themes of highly melancholic songs, focusing on their emotional engagement, interpretation of lyrics and melodies, and the expression of nuanced emotional responses in their comments. Additionally, we explore the alignment between listener feedback and the lyrical themes portrayed in these songs. Our analysis reveals that listener responses encompass a broad spectrum of emotional engagement, including appreciation for the heart-wrenching qualities of the music, the evocation of memories of loved ones, reflections on personal and collective struggles, resilience in the face of adversity, and empathy or compassion for others. These emotional reactions are consistently present across most of the acclaimed sad songs examined in this study, although their intensity and prevalence vary depending on specific factors such as the lyrics, tone, and other musical attributes. Overall, this study provides valuable insights into human emotional resonance with sad music, offering implications for fields such as psychology, emotion research, music therapy, and mental health support.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE International Conference on Big Data, BigData 2024
EditorsWei Ding, Chang-Tien Lu, Fusheng Wang, Liping Di, Kesheng Wu, Jun Huan, Raghu Nambiar, Jundong Li, Filip Ilievski, Ricardo Baeza-Yates, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7161-7170
Number of pages10
ISBN (Electronic)9798350362480
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Big Data, BigData 2024 - Washington, United States
Duration: Dec 15 2024Dec 18 2024

Publication series

NameProceedings - 2024 IEEE International Conference on Big Data, BigData 2024
ISSN (Print)2639-1589
ISSN (Electronic)2573-2978

Conference

Conference2024 IEEE International Conference on Big Data, BigData 2024
Country/TerritoryUnited States
CityWashington
Period12/15/2412/18/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation

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