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Leveraging viewer comments for mood classification of music video clips

Published:28 July 2013Publication History

ABSTRACT

This short paper proposes a method to classify music video clips uploaded to a video sharing service into music mood categories such as 'cheerful,' 'wistful,' and 'aggressive.' The method leverages viewer comments posted to the music video clips for the music mood classification. It extracts specific features from the comments: (1) adjectives in comments, (2) lengthened words in comments, and (3) comments in chorus sections. Our experimental results classifying 695 video clips into six mood categories showed that our method outperformed the baseline in terms of macro and micro averaged F-measures. In addition, our method outperformed the existing approaches that utilize lyrics and audio signals of songs.

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  1. Leveraging viewer comments for mood classification of music video clips

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    • Published in

      cover image ACM Conferences
      SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
      July 2013
      1188 pages
      ISBN:9781450320344
      DOI:10.1145/2484028

      Copyright © 2013 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 July 2013

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      • short-paper

      Acceptance Rates

      SIGIR '13 Paper Acceptance Rate73of366submissions,20%Overall Acceptance Rate792of3,983submissions,20%

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