Voices of Dissent: A Multimodal Analysis of Protest Songs through Lyrics and Audio

Utsav Shekhar, Radhika Mamidi


Abstract
Music has long served as a vehicle for political expression, with protest songs playing a central role in articulating dissent and mobilizing collective action. Yet, despite their cultural significance, the linguistic and acoustic signatures that define protest music remain understudied. We present a multimodal computational analysis of protest and non-protest songs spanning multiple decades. Using NLP and audio analysis, we identify the linguistic and musical features that differentiate protest songs. Instead of focusing on classification performance, we treat classification as a diagnostic tool to investigate these features and reveal broader patterns. Protest songs are not just politically charged they are acoustically and linguistically distinct, and we quantify how.
Anthology ID:
2025.acl-srw.14
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Jin Zhao, Mingyang Wang, Zhu Liu
Venues:
ACL | WS
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Publisher:
Association for Computational Linguistics
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Pages:
213–221
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URL:
https://preview.aclanthology.org/landing_page/2025.acl-srw.14/
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Cite (ACL):
Utsav Shekhar and Radhika Mamidi. 2025. Voices of Dissent: A Multimodal Analysis of Protest Songs through Lyrics and Audio. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 213–221, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Voices of Dissent: A Multimodal Analysis of Protest Songs through Lyrics and Audio (Shekhar & Mamidi, ACL 2025)
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https://preview.aclanthology.org/landing_page/2025.acl-srw.14.pdf