Opinion Mining and Text Analytics of Reader Reviews of Yoko Ogawa's The Housekeeper and the Professor in Goodreads

Abstract

With the development of online social network platforms and social cataloging applications, large amounts of datasets are being generated daily in the form of users' reviews, evaluations, and instant messages. Readers of literary books from around the world now use social media to express their thoughts and feelings about literary works. Collecting and analyzing textual data to gain insight about the readers' interest poses a huge challenge to literary scholars and publishing industries. In this study, the authors aim to apply text analytics methods to analyze and interpret reader responses in the form of book reviews. To this end, they focus on readers' responses and reviews to Yōko Ogawa's The Housekeeper and the Professor (2003) as documented in Goodreads, a social cataloging website that allows readers across the globe to interact with each other about books. The collected data are preprocessed and explored and visualized to gain insight on public opinion about the novel. Finally, the authors analyze the collected data on Goodreads platform by using topic modelling and sentiment analysis in this chapter.