Exploiting Topic Modelling to Classify Sentiment from Lyrics

  • Maibam Debina DeviEmail author
  • Navanath Saharia
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1241)


With the increase in an enormous amount of data, text analysis has become a challenging task. Techniques like classification, categorization, summarization and topic modeling have become part of every natural language processing activity. In this experiment, we aim to perform sentiment class extraction from lyrics using topic modeling techniques. We have use generative statistical model Latent Dirichlet Allocation (LDA) which is also the most widely explored model in topic modeling and another nonparametric bayesian based approach model Heuristic Dirichlet Process (HDP) to extract the topics from 150 lyrics samples of Manipuri songs written using Roman script. We observe this unsupervised techniques, able to obtain the underlying different sentiment class of lyrics in the form of topics.


Lyrics Sentiment classification Topic modelling Latent Dirichlet allocation Hierarchical Dirichlet process 


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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.IIIT ManipurImphalIndia

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