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The Use of Multi-Step Markov Chains in the Characterization of English Literary Works

Authors:
Clement Leung
Chenjie Zeng

Keywords: English literature; Markov model; Multi-step Markov chain; Shakespearean plays; sparse matrix

Abstract:
Typical English literary works tend to include a wide variety of different dimensions and features, and these would constitute the apparatuses which enable individual authors to express their personal sentiments and perspectives in different eras and cultural settings. We make use of iambic pentametre to quantify and characterize such dimensions by the use of Markov chains. Here, we adopt a machine learning approach by processing and extracting the characteristics of known passages and ultimately represent these as a signature transition matrix. We develop a multi-step Markov chain to characterize the time evolution of stress levels. In this approach, arbitrary amount of memory on previous stress levels may be incorporated into the model. It is expected that this method may be further developed and leveraged to enhance understanding and appreciation of English literary works, which will eliminate the application of subjective human judgments.

Pages: 43 to 48

Copyright: Copyright (c) IARIA, 2022

Publication date: November 13, 2022

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-994-2

Location: Valencia, Spain

Dates: from November 13, 2022 to November 17, 2022