Opinion Mining and Text Analytics of Literary Reader Responses

Abstract

Text mining is an important field of study that has proved beneficial for scholars of various disciplines. Literary scholars use text mining to examine the data produced by creative writers, literary readers, publishers, and distributing companies. The produced data are generally in unstructured form that cannot be used to extract useful information. Text mining can discover the unstructured data and convert it to interesting information through several processes. This chapter proposes a text mining technique by using topic modelling and sentiment analysis to retrieve information about the attitude of the user-readers toward the four volumes of KL Noir books on the Goodreads website. The main significance of this approach is to gain the trends by analyzing the book reviews written on Goodreads.