Publicação
Judging books by their covers: predictng success through visual analysis of book covers on goodreads: how text on book covers influence the popularity inside a genre
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | |
| dc.contributor.advisor | Batikas, Michail | |
| dc.contributor.author | Liegeon, Ethan | |
| dc.date.accessioned | 2026-03-31T10:24:44Z | |
| dc.date.available | 2026-03-31T10:24:44Z | |
| dc.date.issued | 2025-01-15 | |
| dc.date.submitted | 2025-01-15 | |
| dc.description.abstract | Using state-of-the-art computer vision algorithms, our research analyzes Goodreads book covers to assess how visual elements influence book popularity across genres, countries, and genders. It provides publishers with targeted cover design recommendations in an increasingly competitive, digital book market. Our research found that book covers significantly influence reader behavior and a book’s popularity. Four analyses revealed that book cover typography signals genres and attracts audiences, gender norms and stereotypes impact cover design and market success, yellow covers in Italian crime novels enhance cultural appeal publishers can leverage, and combining engaging cover designs with impactful reviews further elevates a book’s popularity. | eng |
| dc.identifier.tid | 204133629 | |
| dc.identifier.uri | http://hdl.handle.net/10362/201927 | |
| dc.language.iso | eng | |
| dc.relation | UID/ECO/00124/2013 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Book cover design | |
| dc.subject | Visual analytics | |
| dc.subject | Machine learning | |
| dc.subject | Audience targeting | |
| dc.title | Judging books by their covers: predictng success through visual analysis of book covers on goodreads: how text on book covers influence the popularity inside a genre | eng |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics |