Exploring crosslinguistic and genre variation in syntactic complexity

Insights from a multilingual parallel corpus

Bibliographic Data

ID19485984
AuthorsOlga Nádvorníková (0000-0001-7709-3901, Charles University), Jiří Milička (0000-0001-8605-1199, Charles University), Alexandr Rosen (0000-0003-2210-4268, Charles University)
Year2026
Publication date2026-04-24
Open AccessYes
TypeARTICLE
VenueLinguistics Vanguard (JOURNAL)
Journal identifiersISSN: 2199-174X • E-ISSN: 2199-174X
PublisherWalter de Gruyter GmbH (PUBLISHER • DE)
DOI10.1515/lingvan-2025-0109
OpenAlexW7159832387
LanguageEN
References cited28

Syntactic complexity varies not only between languages but also across textual genres, reflecting structural, stylistic, and communicative factors. This study explores the interplay of these two dimensions by analyzing six syntactic complexity metrics (SCMs) across 17 languages and four genres in a large multilingual corpus. We examine how SCMs correlate across languages and genres and assess which metrics best predict language versus genre. Correlation analysis reveals two robust metric clusters – clausal and phrasal. Inter-metric correlations are high in legal texts and movie subtitles, but substantially lower in parliamentary proceedings and fiction, likely due to greater internal variation in syntactic complexity within these genres. Using random forest classification, we show that SCMs strongly predict genre, with noun phrase metrics ranking highest. In contrast, mean dependency distance (mdd) and its standard deviation are most predictive of language. Misclassification tendencies confirm the affinity of English with Romance languages, previously observed in lexical studies. By emphasizing not only central tendencies (mean values) but also the dispersion of metrics within texts, this study adds methodological nuance to the measurement of syntactic complexity. It also confirms the need to account for both language and genre in crosslinguistic syntactic complexity research

Dependency (UML) · Metric (unit) · Noun phrase · Phrase · Ranking (information retrieval) · Romance languages · Syntax · Variation (astronomy) · Authorship Attribution and Profiling · Second Language Acquisition and Learning · Text Readability and Simplification

Tools

Open DOIOpen Access