Reading_Trends

Fall 2020
5 weeks

Design
Alice Fang
Taery Kim

Development
Joseph Zhang
What do we read   during a pandemic, a financial crisis, after an election? Do books serve as an escape from the present, a source of information and education, or comfort? Do what we search on the web reflect what books they read? 

By retrieving and synthesizing data from Google Trends, New York Times Best Seller Lists, and Google Books API, and generating and comparing classifying keywords for each book using Twinword Text Classification API, we created an interactive experience that visualizes correlations between books on the NYT Best Seller List and Google Trends based on topic and year.

I designed the visual layout and potential interactions, and helped pull and organize data in a very chaotic spreadsheet.

Live Website



Select a Title




Filtering fiction and non-fiction titles




Spreadsheet of book titles

*Our site is a concept visualization. Unfortunately, a lot of false positive correlations were generated. We were limited by the Google searches that we could access, and using the Twinword API generated key words that didn’t necessarily relate contextually to what the book was about.