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The times they are a-changin' (or not): song lyrics analysis over the years

Published: 29 October 2019 Publication History

Abstract

With the growth of music streaming services, the demand for organizing songs according to similarity has increased. In this way, this work proposes to study lyrics of popular songs in order to identify the changes in the vocabulary of the compositions. Analyzing the text, we look for evidences that the themes portrayed by the lyrics undergo changes over the years. When the words used in the compositions do not discriminate years or decades, the context in which those words are inserted causes their meaning to change. Thus, analyzing when certain words occur and how different contexts change their meanings, it is possible to characterize song lyrics temporally. In the future, this analysis can facilitate temporal classification tasks of song lyrics, which can be extended to other types of documents.

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cover image ACM Other conferences
WebMedia '19: Proceedings of the 25th Brazillian Symposium on Multimedia and the Web
October 2019
537 pages
ISBN:9781450367639
DOI:10.1145/3323503
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 29 October 2019

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Author Tags

  1. cultural patterns
  2. natural language processing
  3. temporal data

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WebMedia '19
WebMedia '19: Brazilian Symposium on Multimedia and the Web
October 29 - November 1, 2019
Rio de Janeiro, Brazil

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Overall Acceptance Rate 270 of 873 submissions, 31%

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