Information Systems Education Journal


V20 N3 Pages 44-60

Jun 2022

Bracketology: Predicting Winners from Music March Madness

Kevin Mentzer
Nichols College
Dudley, MA USA

Zachary Galante
Bryant University
Smithfield, RI USA

Mark Frydenberg
Bentley University
Waltham, MA USA

Abstract: Organizations are keenly interested in data gathering from websites where discussions of products and brands occur. This increasingly means that programmers need an understanding of how to work with website application programming interfaces (APIs) for data acquisition. In this hands-on lab activity, students will learn how to gather data from several prominent websites using APIs and then build predictive models using that data. Unlike popular challenges on competition sites such as Kaggle where challenges often supply the data, this project emphasizes the data acquisition step of the analytics lifecycle. Working with data from Spotify, YouTube, and Twitter, students will fill out a music based March Madness bracket to predict the winner of the annual Locura De Marzo, a popular middle and high school Spanish competition. By becoming familiar with the data available from each site, through the analysis of the JSON formatted data returned by the APIs, students will be able to explore which features of a song might lend themselves to higher voting by high school students in order to build better prediction models.

Download this article: ISEDJ - V20 N3 Page 44.pdf

Recommended Citation: Mentzer, K., Galante, Z., Frydenberg, M., (2022). Bracketology: Predicting Winners from Music March Madness. Information Systems Education Journal20(3) pp 44-60. ISSN : ISSN: 1545-679X. A preliminary version appears in The Proceedings of EDSIGCON 2021