Entropy-based syntactic tree analysis for text classification: a novel approach to distinguishing between original and translated Chinese texts

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AP9YL4LRB" target="_blank" >RIV/00216208:11320/25:P9YL4LRB - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201389489&doi=10.1093%2fllc%2ffqae030&partnerID=40&md5=903d2c494ee2da621b0b7bbc69e53087" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201389489&doi=10.1093%2fllc%2ffqae030&partnerID=40&md5=903d2c494ee2da621b0b7bbc69e53087</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/llc/fqae030" target="_blank" >10.1093/llc/fqae030</a>

Result language

angličtina

Original language name

Entropy-based syntactic tree analysis for text classification: a novel approach to distinguishing between original and translated Chinese texts

Original language description

This research focuses on classifying translated and non-translated Chinese texts by analyzing syntactic rule features, using an integrated approach of machine learning and entropy analysis. The methodology employs information entropy to gauge the complexity of syntactic rules in both text types. The methodology is based on the concept of information entropy, which serves as a quantitative measure for the complexity inherent in syntactic rules as manifested from tree-based annotations. The goal of the study is to explore whether translated Chinese texts demonstrate syntactic characteristics that are significantly different from those of non-translated texts, thereby permitting a reliable classification between the two. To do this, the research calculates information entropy values for syntactic rules in two comparable corpora, one of translated and the other of non-translated Chinese texts. Then, various machine learning models are applied to these entropy metrics to identify any significant differences between the two groups. The results show significant differences in the syntactic structures. Translated texts have a higher degree of entropy, indicating more complex syntactic constructs compared to non-translated texts. These findings contribute to our understanding of the effect of translation on language syntax, with implications for text classification and translation studies. © The Author(s) 2024.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Digital Scholarship in the Humanities

ISSN

2055-7671

e-ISSN

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Volume of the periodical

39

Issue of the periodical within the volume

3

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

984-1000

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85201389489