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Analyzing Linguistic Differences in Academic English: A Graph-Based Machine Learning Approach
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Author(s): Krishna Kumari R. (Department of Mathematics, SRM Institute of Science and Technology, Kattankulathur, India)and Ami Femila P. (Department of English and Foreign Languages, SRM Institute of Science and Technology, Kattankulathur, India)
Copyright: 2025
Pages: 20
Source title:
Optimizing Research Techniques and Learning Strategies With Digital Technologies
Source Author(s)/Editor(s): J. Sadhik Basha (International Maritime College Oman, National University of Science and Technology, Oman), Taofeek Olanrewaju Alade (Department of Science Cluster, International Maritime College Oman, National University of Science and Technology, Oman), Mitha Obaid Amur Al Khazimi (Department of Science Cluster, National University of Science and Technology, Oman), Ranjit Vasudevan (Department of Science Cluster, National University of Science and Technology, Oman)and Jahanzeb Bahadur Khan (Department of Science Cluster, National University of Science and Technology, Oman)
DOI: 10.4018/979-8-3693-7863-2.ch011
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Abstract
This study employs graph-based machine learning techniques to explore and analyze the linguistic differences between the English used by Indian and British academicians. By constructing language graphs from academic texts, we identify distinct patterns, syntactic structures, and semantic variations. These graphs represent sentences as nodes and relationships, such as co-occurrences or syntactic dependencies, as edges. Our approach leverages advanced community detection algorithms to uncover clusters of linguistically similar nodes and node centrality measures to identify key terms or structures that dominate regional writing styles. Additionally, we incorporate semantic network analysis to understand contextual nuances and word usage. By combining these techniques, we reveal underlying linguistic characteristics and trends, offering novel insights into regional variations in academic writing, which can have significant implications for cross-cultural communication, education, and global academic collaborations.
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