Yucesoyetal.EPJ Data Science (2018)7:7 https://doi.org/10.1140/epjds/s13688-018-0135-y REGULAR ARTICLE OpenAccess Success in books: a big data approach to bestsellers Burcu Yucesoy1,XindiWang1, Junming Huang1,2 and Albert-László Barabási1,3,4,5* *Correspondence:
[email protected] Abstract 1Center for Complex Network Research and Department of Reading remains the preferred leisure activity for most individuals, continuing to offer Physics, Northeastern University, a unique path to knowledge and learning. As such, books remain an important Boston, USA cultural product, consumed widely. Yet, while over 3 million books are published each 2CompleX Lab, Web Sciences Center, University of Electronic year, very few are read widely and less than 500 make it to the New York Times Science and Technology of China, bestseller lists. And once there, only a handful of authors can command the lists for Chengdu, China more than a few weeks. Here we bring a big data approach to book success by Full list of author information is available at the end of the article investigating the properties and sales trajectories of bestsellers. We find that there are seasonal patterns to book sales with more books being sold during holidays, and even among bestsellers, fiction books sell more copies than nonfiction books. General fiction and biographies make the list more often than any other genre books, and the higher a book’s initial place in the rankings, the longer the book stays on the list as well. Looking at patterns characterizing authors, we find that fiction writers are more productive than nonfiction writers, commonly achieving bestseller status with multiple books.