Introduction to Artificial Intelligence for the Analytics of Literary Works and Social Media: A Review

Introduction

The rapid growth in the publishing industry and the emergence of internet and social media platforms have dramatically impacted the ways in which books are published, distributed, purchased, read, and reviewed. On the one hand, the onset of the digital age in the final decades of the twentieth century has greatly minimized the need for big publishing houses to be the linking chain between the writer and the reader. The emergence of internet-based self-publishing platforms, for example, has allowed fiction and non-fiction writers to get their books directly into the hands of their fans and readers. Likewise, the surge of social media platforms such as Facebook and Twitter as well as social cataloging websites such as Goodreads have provided the fans and readers around the world with a unique opportunity to communicate with each other and share with the world their feedback and feelings about literary works (Keikhosrokiani & Asl, 2022). Readers’ responses and feedback documented in these platforms are of great importance to companies and organizations whose benefits lie in comprehending the current trends. Previous studies have underlined the significance of readers’ criticism and sentiments both in assigning meaning to a text and in its market success or failure (Al Mamun et al., 2022; Chu et al., 2022; Fasha et al., 2022; Sofian et al., 2022; Suhendra et al., 2022). On the other hand, the massive rise in the number of published materials and the huge number of opinions shared in the digital world have created a considerable amount of data that can no longer be handled with traditional ways of data analysis. For instance, the conventional method of manual text analysis proves to be inadequate and ineffective when it comes to the analysis of such big data. For a long time, the manual data analysis of literary narratives has been criticized for inaccuracy, bias, and prejudice. The inaccuracy seems to be particularly evident in the study of literary representations and readers’ voicing of their sentiments with regards to the prevailing themes of a literary text.

Contemporary developments in Artificial Intelligence have appeared as promising substitutes to traditional ways of data collection and data analysis. The adoption and deployment of computerized analytical techniques have to a great extent eliminated or resolved the problems of inaccuracy and subjectivity in the analyses of literary works and the studies of readers’ responses to fictional stories. Previous studies have used techniques such as Opinion Mining, and Text Analytics methods such Topic Modelling and Sentiment Analysis to examine the themes, settings, characterizations, storyline, readers’ responses, sentiments, and opinions (Asri et al., 2022; Fasha et al., 2022; Keikhosrokiani & Asl, 2022; Paremeswaran et al., 2022; Sofian et al., 2022; Suhendra et al., 2022). Of the many studies, one can note the adoption of Artificial Intelligence in the study of the connection between theme, place, and sentiment in English narratives by writers from the Middle East and South Asia. The stories from these regions have been the subject matter of public and critical controversy, and the employment of computerized techniques in the analysis of those stories have proved highly beneficial for literary critics and scholars (Asl, 2022). In a similar way, studies have shown that book club judges, literary prize-givers, and publishing industries have benefited extremely in their decision makings from the application of Artificial Intelligence techniques in the study of literary fans and enthusiasts’ sentiments and reactions to certain stories (Paremeswaran et al., 2022). In like manner, the developments in computer sciences and information technology have been useful to geographers and feminist geographers in the spatial mapping of certain events, characters, or themes in fictional worlds. An example of such a study is conducted by Jafery et al. (2022) where the authors explore a corpus of six life writings by or about Iraqi people to identify the connection between theme, place, and sentiment. In continuation of such studies, the present book aims to present contemporary developments in the adoption of artificial intelligence in textual analysis of literary works and social media, and hence to provide a multidisciplinary approach related to fields of computer science, data science, social sciences, and literary studies. Therefore, theories, approaches, techniques, models, and applications of artificial intelligence, which can be used to analyze data related to literary works and social media, will be introduced in this book.