Distribution of dependency tags in different text types in Czech

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17250%2F25%3AA2603CPM" target="_blank" >RIV/61988987:17250/25:A2603CPM - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:90244/25:10513827

Výsledek na webu

<a href="https://benjamins.com/catalog/cilt.370.08che" target="_blank" >https://benjamins.com/catalog/cilt.370.08che</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1075/cilt.370.08che" target="_blank" >10.1075/cilt.370.08che</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Distribution of dependency tags in different text types in Czech

Popis výsledku v původním jazyce

The objective of this chapter is to examine how dependency tags are distributed across various genres in the Czech language. Specifically, our focus is on identifying the similarities and differences in these distributions among different types of text. This study utilizes data from the SYN2020, a large balanced corpus of contemporary written Czech, comprising 100 million words. The findings indicate that the frequencies of dependency tags follow a power-law distribution, represented by the equation y = ax-b. When analyzing the values of the parameters a and b, a distinct pattern emerges that differentiates the genres. Genres within fiction, such as poetry, drama, novels, and short stories, typically exhibit lower values for a and b, whereas non-fiction genres, including administrative texts and professional literature, demonstrate higher values. Journalistic texts, like newspapers and leisure magazines, fall in between fiction and non-fiction literature in terms of these parameter values. Consequently, comparing these parameters appears to be an effective method for conducting stylometric research.

Název v anglickém jazyce

Distribution of dependency tags in different text types in Czech

Popis výsledku anglicky

The objective of this chapter is to examine how dependency tags are distributed across various genres in the Czech language. Specifically, our focus is on identifying the similarities and differences in these distributions among different types of text. This study utilizes data from the SYN2020, a large balanced corpus of contemporary written Czech, comprising 100 million words. The findings indicate that the frequencies of dependency tags follow a power-law distribution, represented by the equation y = ax-b. When analyzing the values of the parameters a and b, a distinct pattern emerges that differentiates the genres. Genres within fiction, such as poetry, drama, novels, and short stories, typically exhibit lower values for a and b, whereas non-fiction genres, including administrative texts and professional literature, demonstrate higher values. Journalistic texts, like newspapers and leisure magazines, fall in between fiction and non-fiction literature in terms of these parameter values. Consequently, comparing these parameters appears to be an effective method for conducting stylometric research.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

60203 - Linguistics

Projekt

<a href="/cs/project/GA22-20632S" target="_blank" >GA22-20632S: Kvantitativní syntaktická stylistika současné psané češtiny</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Mathematical Modelling in Linguistics and Text Analysis

ISBN

9789027228376

Počet stran výsledku

14

Strana od-do

90-103

Počet stran knihy

241

Název nakladatele

John Benjamins Publishing Company

Místo vydání

Amsterdam

Kód UT WoS kapitoly

001609792500009