Savitribai Phule Pune University |
Title | Mining of Large Scale Lyrics Data |
Speaker |
Dr. Amit Awekar,
IIT Guwahati
Dr. Amit Awekar is an Assistant Professor in Computer Science and Engineering Department of IIT Guwahati. He completed his PhD in Computer Science from North Carolina University where his dissertation topic was ‘Fast, Incremental, and Scalable All Pairs Similarity Search’. Dr. Awekar’s current research interests include data-mining algorithms for dynamic data sets, near duplicate detection, knowledge graph construction from natural language text, etc. |
Date & Time | Thursday, 09 January 2020 | 15:30-16:30 |
Venue | Kelkar Lab, CMS |
Abstract | The central idea of the work that I will present is to gain a deeper understanding of song lyrics computationally. We focus on two aspects: style and biases of song lyrics. In this work, we analyzed more than half a million songs spread over five decades. We characterize the lyrics style in terms of vocabulary, length, repetitiveness, speed, and readability. We have observed that the style of popular songs significantly differs from other songs. We have used distributed representation methods and WEAT test to measure various gender and racial biases in the song lyrics. We have observed that biases in song lyrics correlate with prior results on human subjects. This correlation indicates that song lyrics reflect the biases that exist in society. Increasing consumption of music and the effect of lyrics on human emotions makes this analysis important. |
Organizer/Host | Farhad (farhad.panthaki@cms.unipune.ac.in), Harshit (harshit.agrawal@cms.unipune.ac.in) |
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