A Novel Model to Predict a Book's Success in the New York Times Best Sellers List

(1) San Marino High School, San Marino, CA, (2) Clements High School, Sugar Land, TX, (3) The Lawrenceville School, Lawrenceville, NJ, (4) Dougherty Valley High School, San Ramon, CA

The popularity of media, such as books and music, has historically been considered difficult to forecast. This popularity is important in determining the success that can be achieved once the media is published. Therefore, we aim to evaluate the extent to which this fact holds true, as we propose that these public opinion trends are quite deterministic in nature. We investigated the important non-textual attributes determining a book’s popularity, including but not limited to a book’s previous ranking in the New York Times Best Sellers list and its popularity in searches. We then constructed two models: a generalized classifier of a successful Best Seller and a predictor of a book’s weekly rank on the New York Times Best Sellers list. The reasonable accuracy of our classification and regression models suggest that book popularity is indeed deterministic. These findings point towards definitive characteristics that can help creators produce successful works.

A4b52e4e0eb4c7f3cdae9149b622f4580552e02b
Download Full Article as PDF

This article has been tagged with:

computer science modeling consumer behavior
Support JEI!