Date of Award
University Scholars Director
Dr. Christine Chaney
First Advisor/Committee Member
Dr. Peg Achterman
Second Advisor/Committee Member
Dr. Carlos Arias
Content Analysis, Book Recommendation, Recommender System, Mobile Application
Book recommendation applications combine word-of-mouth recommendations with algorithms that can suggest books based on a user’s account activity, creating a robust system for finding new books to read. Current research on recommendation systems is purely quantitative, focusing on the efficacy of the system, and content analyses are only just beginning to be performed on mobile applications. I use previous content analyses on applications as a basis for creating a content analysis framework for book recommendation applications. This framework can be used to analyze what users find important in book recommendation apps and inform app creators about their users’ wants and needs.
Payne, Cypress S., "Read This: A Content Analysis Framework for Book Recommendation Applications" (2022). Honors Projects. 176.
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