This track explores the application of corpus linguistics in the analysis of English literary texts. It aims to uncover patterns and trends in language use, enhancing our understanding of literary styles and themes.

Focusing on quantitative approaches, this track examines how statistical methods can be employed to analyze linguistic phenomena. Participants will discuss the implications of data-driven research in linguistics.

This session investigates the integration of machine learning techniques in the field of textual analysis. Researchers will present case studies demonstrating the effectiveness of these methods in uncovering insights from large text corpora.

This track addresses the intersection of digital humanities and literary studies, emphasizing innovative computational methods. Discussions will center on how digital tools can reshape our understanding of literary history and criticism.

Focusing on the semantic dimensions of poetry, this track invites contributions that utilize computational methods to analyze poetic texts. Participants will explore how semantic structures contribute to the aesthetic and emotional impact of poetry.

This session delves into the advancements in language modeling and their applications in various linguistic contexts. Researchers will discuss the implications of these models for understanding language structure and use.