Analysis of Nigeria’s Top Ten Song Lyrics Using Natural Language Processing Techniques

Authors

  • Seun Ebiesuwa, Tolulope Amos Awoniyi, Olawunmi Asake Adebanjo, Adesoji Adegbola, Mgbeahuruike Emmanuel, Adelowo Opeyemi Joshua, Adedoyin Adebanjo, Oladipo Sunday Oluwadare, Falana Taye Oluwaseun, Oyerinde Emmanuel Ifeoluwa

Keywords:

LDA techniques, Lyrics, Music, Natural language processing, Sentiment analysis

Abstract

The inclusion of lyrics in music enhances its depth and significance by providing a medium for songwriters to express their thoughts, emotions, and experiences. This study aims to analyze the lyrical content of the top 10 Nigerian songs on Spotify using natural language processing techniques. Music consumption platforms such as Spotify play a pivotal role in shaping musical preferences and cultural influences. As the Nigerian music industry continues to thrive, understanding the lyrical content of the top 10 songs on platforms such as Spotify becomes essential. This study examines the top 10 songs Nigerian weekly music chart on November 1 2023 to ensure that the analysis is relevant and reflective of current trends in contemporary music. By exploring the linguistic richness, cultural nuances, and emotional expressions embedded in the lyrics, this study seeks to provide an insightful understanding of how Nigerian music is evolving on a global streaming platform. The methodology involves systematic data collection, thorough text preprocessing, and the use of natural language processing (NLP) tools. Most songs showcased a positive sentiment, focusing on themes such as celebration, joy, and empowerment. Love and optimism were also prominent elements of the lyrical content. Sample generated lyrics that resemble the style of the song were presented.

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Published

26.11.2024

How to Cite

Seun Ebiesuwa. (2024). Analysis of Nigeria’s Top Ten Song Lyrics Using Natural Language Processing Techniques . International Journal of Intelligent Systems and Applications in Engineering, 12(4), 4431–4438. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/7077

Issue

Vol. 12 No. 4 (2024)

Section

Research Article

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