LEXICAL PATTERNING IN SHAKESPEAREAN TRAGEDIES: A CORPUS-BASED ANALYSIS USING SKETCH ENGINE THROUGH THE LENS OF LEXICAL PRIMING THEORY

Abstract

This study investigates lexical patterning in selected Shakespearean plays (All’s Well That Ends Well, The Merchant of Venice, Julius Caesar, and Hamlet) using corpus-based tools, with a theoretical lens drawn from Michael Hoey’s Lexical Priming Theory. By constructing a customized corpus in Sketch Engine, the study focuses on key lexical items—love, grief, father, sad, good, and hate—to analyze frequency, collocational patterns, parts of speech, and n-grams. The analysis reveals how repeated exposure to specific lexical items contributes to meaning-making, character construction, and thematic development in Shakespearean tragedies. The findings aim to provide deeper cognitive and linguistic insight into Shakespeare’s stylistic use of language, with implications for literary interpretation and digital humanities research.