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Lexical diversity in kinship across languages and dialects
Hadi Khalilia1,2, Gábor Bella3, Abed Alhakim Freihat1
1Department of Information Engineering and Computer Science, University of Trento, Trento, Italy.
Frontiers in Psychology
|December 6, 2023
Summary
This study introduces a new method to represent linguistic diversity in computational lexicons. Case studies on Arabic and Indonesian kinship terms reveal significant diversity even within closely related languages.
Area of Science:
- Computational linguistics
- Lexicography
- Linguistic anthropology
Background:
- Lexicons often fail to represent the full diversity of language, including phenomena like lexical gaps and untranslatability.
- Existing computational lexical resources lack comprehensive data on linguistic diversity.
- Kinship terminology is a well-documented area of linguistic and cultural diversity.
Purpose of the Study:
- To introduce and validate a method for enriching computational lexicons with linguistic diversity content.
- To computationally represent and analyze diversity in kinship terminology across different languages and dialects.
- To provide insights into the extent of linguistic diversity within culturally and linguistically proximate communities.
Main Methods:
- Developed a novel method for incorporating linguistic diversity into computational lexicons.
- Conducted two large-scale case studies focusing on kinship terminology.
- Analyzed kinship terms across seven Arabic dialects and three Indonesian languages.
Main Results:
- Successfully enriched computational lexicons with data on linguistic diversity.
- Quantified and visualized diversity in kinship terminology within Arabic and Indonesian language groups.
- Demonstrated the method's effectiveness in capturing nuanced linguistic variations.
Conclusions:
- The proposed method effectively enhances computational lexicons with linguistic diversity.
- Significant linguistic diversity in kinship terms exists even within closely related language communities.
- The generated resources offer valuable data for linguistics research and computational applications.
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