About

The asset of our project is the extensive dataset sourced from the Billboard Hot 100 table from 1960 to 2020, which is also the backbone of our project. This dataset includes information such as the unique ID of the recording, artist name, track name and date of the first entry into the Billboard Hot 100. It also includes details about harmonic and timbral topics, chord change counts and timbre class counts which can help analyze the technical characteristics of the tracks. Our dataset allows us to illustrate aspects of popular music and its transformation over time and it also acknowledges its limitations in representing other important aspects of music expression such as the absence of racial and emotional influence of music.

Our research project employs several software and computational methodologies to create visualizations. Our images are largely from Python Matlibplot, seaborn, and Google search engine. Texts are fully created by our team members. We chose to use Google Sites for our project because of the various functions that Google Sites provided, making it easy for us to collaborate and design our web. We also use Google Sites' built-in hosting function to host our website.

The interface or the user experience of our website is designed to be accessible, interactive and engaging. We offer various ways for users to interact with the data. Users can explore the data through different visualizations, such as word cloud, bar chart, line chart and heatmap. For accessibility, we have put alt-text for all images on our websites. We also linked the full interactive tableau dashboard onto our websites.

Meet the team

Grace Qian

A rising junior majoring in Industrial Engineering and Operations Research (IEOR) and minoring in Data Science. Grace was the one who first found out about this project and added it onto Dr. Scott Caddy’s page! Grace contributed to the writing of all breakdowns of the project, specificaly the storyboard, narrative, and the website's narrative page! A fun fact about Grace is that she can deadlift 275 lbs.

Qiuxuan Li

A fourth-year Statistics major planning to minor in Data Science at Cal. Qiuxuan contributed to data visualizations and the writing of all the breakdowns of the project, including the storyboard, narrative, annotated bibliography, data critique and the about page. A fun fact about her is that she has a corgi.

WingYeung Ma

A fourth-year Data science major at the University of California, Berkeley. WingYeung contribute to the general management of the projects, make sure deadlines are met. Additionally, he contribute to the data sources, data wrangling, data visualizations, and programming with LDA.

Qihua Xue

A fourth-year student majoring in Applied Mathematics and Data Science at UC Berkeley. Qihua contributed to the writing of all breakdowns of the project, including storyboard, narrative, annotated bibliography, and data critique.

Lyuheng Zheng

A fourth-year student majoring in Environmental Economics & Policy and Data Science(declaring) at UC Berkeley. Lyuheng helps the group to research, analyze and edit contents, including storyboard, narrative, several sources on annotated bibliography, data critique and the about page.

Acknowledgments

Our team would like to express our gratitude to all those who have contributed to the completion of this digital humanities project. First, we would like to acknowledge and thank Professor Caddy and Professor James of DigHum100 for guiding us through the necessary skills and deadlines to complete this project. Second, we would like to thank our Graduate Student Instructor Prashant Sharma for helping answer all the questions we had and helping us code in LDA. Furthermore, we would like to say thank you to the University of California, Berkeley, and their libraries. They provided us with necessary resources, and technical support for this project.

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