Exploring the application of artificial intelligence in English literary criticism: a Delphi and AHP-based thematic analysis

Abstract

Abstract The integration of artificial intelligence (AI) in various fields has revolutionized traditional methods, introducing innovative tools and approaches. In the realm of English literary criticism (ELC), AI offers novel possibilities for textual analysis, authorship attribution, thematic exploration, and more. Despite its potential, there is a significant paucity of robust studies that systematically explore these applications through structured methodologies. This article aims to fill this gap by employing the Delphi method and analytic hierarchy process (AHP) to identify and prioritize the key applications and components of AI in English literary criticism. To this end, the applications of AI in ELC were initially extracted through thematic analysis of previous literature. The Delphi method was then used to refine and finalize this list by consulting a panel of experts. Following this, the AHP was employed to determine the importance and prioritize each application based on expert evaluations. The applied method identified eleven key applications of AI in ELC, each with its own set of critical components. The AHP analysis provided a hierarchical structure, prioritizing these applications and components based on their importance and feasibility. The top applications identified include textual analysis, authorship attribution, and digital humanities. Within these applications, specific components such as sentiment analysis, stylometry, and thematic detection were highlighted as highly impactful. These findings offer valuable insights for researchers and practitioners, guiding future developments and implementations of AI technologies in literary criticism.

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