Read to grow: exploring metadata of books to make intriguing book recommendations for teenage readers

It is clearly established that spending time reading is beneficial for an individual’s development in terms of their social, emotional, and intellectual capabilities. This is especially true for teenagers who are in the growing process and reading can improve their memory, vocabulary, concentration and attention span, creativity and imagination, and writing skills. With the overwhelming volume of (online) books available these days, it becomes a huge challenge to find suitable and appealing books to read. Current book recommender systems, however, do not adequately capitalize teenagers’ specific needs such as readability levels, emotional capabilities, and subject’s comprehension, that are more at the forefront for teenage readers than adults and children. To make appropriate recommendations on books for teenagers, we propose a book recommender system, called TBRec. TBRec recommends books to teenagers based on their personal preferences and needs that are determined by using various book features. These features, which include book genres, topic relevance, emotion traits, readers’ advisory, predicted user rating, and readability level, have significant impact on the teenagers’ preference and satisfaction on a book. These distinguished parts of a book, which are premeditated and essential criteria for book selection, identify the type, subject area, state of consciousness, appeal factors, (un)likeness, and complexity of the book content, respectively. Experimental results reveal that TBRec outperforms Amazon, Barnes and Noble, and LibraryThing, three of the widely used book recommenders, in making book recommendations for teenagers, and the results are statistically significant.