Artificial Intelligence Applications in Literary Works

Abstract

The British Pakistani writer, Mohsin Hamid's debut novel, Moth Smoke (2000), has garnered conflicting responses from readers across the globe. Over the past few years and with the rapid advancements in social media platforms, readers around the world have publicly shared their opinions and feelings towards the text using online platforms such as Twitter, Goodreads, Facebook—among many others. The huge bulk of readers' reviews are useful data for publishers and booksellers in analyzing readers' interests to recommend similar texts to online readers. The analysis of sentiment and emotion attached to this data can help to determine the popularity or unpopularity of a literary text. Using reader-reviews of Hamid's novel from Goodreads as the main data source, this study a offers a data analytic approach: LSTM, LDA to detect and classify the dominant emotion existing within the readers' feedback. Understanding readers' emotions towards the novel can help in developing a recommendation system that can suggest readers stories of their interest.