A Study on Using Semantic Word Associations to Predict the Success of a Novel

Proceedings of the 10th Conference on Lexical and Computational Semantics, pages 38–51 August 5–6, 2021, Bangkok, Thailand (online) ©2021 Association for Computational Linguistics 38 A Study on Using Semantic Word Associations to Predict the Success of a Novel Syeda Jannatus Saba*1, Biddut Sarker Bijoy*1, Henry Gorelick2, Sabir Ismail3, Md Saiful Islam1, Mohammad Ruhul Amin2 1Department of Computer Science & Engineering, Shahjalal University of Science & Tech. 2Department of Computer & Information Science, Fordham University 3Google LLC {syeda06,biddut12}@student.sust.edu, hgorelick@fordham.edu, sabir.ismail01@gmail.com, saiful-cse@sust.edu,mamin17@fordham.edu Abstract Many new books get published every year, and only a fraction of them become popular among the readers. So the prediction of a book suc- cess can be a very useful parameter for pub- lishers to make a reliable decision. This ar- ticle presents the study of semantic word as- sociations using the word embedding of book content for a set of Roget’s thesaurus concepts for book success prediction. In this work, we discuss the method to represent a book as a spectrum of concepts based on the association score between its content embedding and a global embedding (i.e. fastText) for a set of se- mantically linked word clusters. We show that the semantic word associations outperform the previous methods for book success prediction. In addition, we present that semantic word as- sociations also provide better results than us- ing features like the frequency of word groups in Roget’s thesaurus, LIWC (a popular tool for linguistic inquiry and word count), NRC (word association emotion lexicon), and part of speech (PoS). Our study reports that con- cept associations based on Roget’s Thesaurus using word embedding of individual novel re- sulted in the state-of-the-art performance of 0.89 average weighted F1-score for book suc- cess prediction. Finally, we present a set of dominant themes that contribute towards the popularity of a book for a specific genre. 1 Introduction Every year a lot of literary fictions get published and only a few of them achieve the popularity. So it is very important to be able to predict the success of a book before the publisher commits a signifi- cant effort and resources for it. Many factors con- tribute to the success of a book. The story, plot, and character development, all have specific role in the popularity of a book. There are some other factors *Both authors contributed equally to this research. Figure 1: This figure represents average word embed- ding association scores for 24 themes as defined in the Roget’s thesaurus. We observe that corresponding as- sociation scores for historical fiction books, such as the successful book The Prince and the Pauper, and the unsuccessful book The House of the Seven Gables are very different. The success of those books were defined using their corresponding Goodreads-rating. like the time when the book has been published, the author’s reputation, the marketing strategy, etc that may also influence a book’s popularity. In this paper, we only focus on understanding a set of con- cepts’ associations extracted from the content of the book to predict …

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