Quantitative Approaches to the Study of Russian Dialects

This dissertation provides a quantitative analysis of Russian dialects in the European part of Russia. Drawing on the Dialectological Atlas of the Russian Language, which documents dialect features from approximately 4200 survey sites, the study develops a quantitative classification of Russian dialects and investigates the linguistic features underlying this classification. The analysis is based on a digitized and systematically prepared version of the atlas data, comprising more than one million data points. Linguistic distances between survey sites are calculated using a recursive normalized variant of the Hamming distance and are subsequently analyzed through hierarchical clustering. After evaluating several clustering methods and validation measures, the study proposes a four-cluster WPGMA classification that distinguishes Northern, Central-Eastern, Central-Western, and Southern Russian dialect areas. In a second step, the dissertation characterizes these clusters linguistically by combining frequency-based analysis with Normalized Pointwise Mutual Information (nPMI). The results confirm major established distinctions in Russian dialectology, particularly the opposition between Northern and Southern dialects, while also providing novel results on the specific features (phonetic, lexical, morphological, and syntactic features) associated with individual dialect clusters.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Christian-Albrechts-Universität zu Kiel

Year

2026

Author dc:creator

• Jonjić, Darja

Contributors dc:contributor

• Nübler, Norbert
• Wichmann, Søren

• Russian dialects
• dialectometry
• dialect classification
• Dialectological Atlas of the Russian Language
• hierarchical clustering
• cluster validation
• WPGMA
• Normalized Pointwise Mutual Information

Repository record source_url

https://macau.uni-kiel.de/receive/macau_mods_00008692

OAI record oai:identifier

https://macau.uni-kiel.de/servlets/OAIDataProvider?verb=GetRecord&metadataPrefix=xMetaDissPlus&identifier=oai%3Amacau.uni-kiel.de%3Amacau_mods_00008692