Stylomech: Unveiling Authorship via Computational Stylometry in English and Romanized Sinhala
Nabeelah Faumi, Adeepa Gunathilake, Benura Wickramanayake, Deelaka, Dias, TGDK Sumanathilaka

TL;DR
This paper introduces a novel computational stylometry method for authorship attribution in English and Romanized Sinhala, focusing on comparing pairs of texts to enhance content verification and address intellectual property issues.
Contribution
It presents a unique approach that compares only two texts using numerical representations, expanding authorship attribution to less-explored linguistic contexts like Romanized Sinhala.
Findings
Effective in distinguishing authors with limited text comparison
Applicable to multiple languages including Sinhala and English
Enhances trust and accountability in digital content
Abstract
With the advent of Web 2.0, the development in social technology coupled with global communication systematically brought positive and negative impacts to society. Copyright claims and Author identification are deemed crucial as there has been a considerable amount of increase in content violation owing to the lack of proper ethics in society. The Author's attribution in both English and Romanized Sinhala became a major requirement in the last few decades. As an area largely unexplored, particularly within the context of Romanized Sinhala, the research contributes significantly to the field of computational linguistics. The proposed author attribution system offers a unique approach, allowing for the comparison of only two sets of text: suspect author and anonymous text, a departure from traditional methodologies which often rely on larger corpora. This work focuses on using the…
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Taxonomy
TopicsAuthorship Attribution and Profiling
