Analyzing Audio Features Across Genres to Understand Song Popularity: A Data-Driven Approach Using Spotify API
Project by Polygence alum Aditya
Project's result
The outcome from this project includes a research paper of the full analysis of the process. This project has been submitted and accepted to a journal and further research could be done to modify and expand upon the content.
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Summary
This project investigates an overview of which main audio features define the popularity of any song genre. The dataset was gathered through the Spotify API and was tested using statistical methods and correlations. In this paper, 1,000 tracks of four genres are used: pop, rock, hip-hop, and country. Statistical methods of t-test and correlation matric have been applied to key features: tempo, energy, danceability, valence, and acousticness. These features were then used to identify significant patterns and trends related to song popularity. According to the findings, tempo, energy, and valence result to be the most correlated features with song popularity, although these relations are quite different across genres.
Won
Polygence mentor
PhD Doctor of Philosophy
Subjects
Computer Science, Quantitative
Expertise
Machine Learning, Security, Privacy, Data Science, Statistics, Computer Science
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Aditya
Student
Graduation Year
2026
Project review
“Working on this statistical analysis project, which involved the use of the Spotify API, was an incredibly enriching experience. Delving into the stats, identifying patterns, and applying statistical methods allowed me to truly deepen my understanding of both theoretical and practical aspects of statistical analysis and data science. The project challenged me to think critically, troubleshoot issues, and continuously refine my approach to ensure accuracy and relevance in my findings. It was both demanding and rewarding to see how my raw data could be transformed into meaningful insights through careful analysis, making me grateful for the amazing experience.”
About my mentor
“My experience with my mentor was invaluable throughout this journey. From the very beginning, they provided their utmost honesty and clear guidance on how the project should be structured and were comfortable with any changes that were made throughout the project as well. Their feedback was always constructive, pushing me to think deeper and approach problems from different angles. Whenever I faced challenges throughout the project, my mentor was always there to offer support, suggest resources, and encourage me to find new ways to arrive at the end solution independently. Their mentorship not only helped me progress throughout the journey of this paper but also significantly improved my research and analytical skills, which I will carry forward in my academic and professional endeavors.”
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