Statistical Modeling of Discourse Genres: The Case of the Opinion Column in Spanish

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AYS6YBZ2Q" target="_blank" >RIV/00216208:11320/25:YS6YBZ2Q - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206371953&doi=10.1007%2fs42979-024-03329-8&partnerID=40&md5=6a263ccbd549f2fec376c4db7daaf521" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206371953&doi=10.1007%2fs42979-024-03329-8&partnerID=40&md5=6a263ccbd549f2fec376c4db7daaf521</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s42979-024-03329-8" target="_blank" >10.1007/s42979-024-03329-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Statistical Modeling of Discourse Genres: The Case of the Opinion Column in Spanish

Popis výsledku v původním jazyce

This paper presents a statistical model of the opinion column, a discourse genre typical of the press. The model was derived from a relatively small sample (ca. 4000 texts), and it takes into account discourse variables such as text and paragraph length, discourse markers, deixis and modalization. In order to test the accuracy of the model, it was evaluated against a different corpus of mixed column and non-column documents. The idea was to test whether the model is able to identify those texts pertaining to the target genre. Results show that it is indeed accurate, with results ranging from 85 to 77% precision and 40–61% recall, depending on how restrictive the application of the model is. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

Název v anglickém jazyce

Statistical Modeling of Discourse Genres: The Case of the Opinion Column in Spanish

Popis výsledku anglicky

This paper presents a statistical model of the opinion column, a discourse genre typical of the press. The model was derived from a relatively small sample (ca. 4000 texts), and it takes into account discourse variables such as text and paragraph length, discourse markers, deixis and modalization. In order to test the accuracy of the model, it was evaluated against a different corpus of mixed column and non-column documents. The idea was to test whether the model is able to identify those texts pertaining to the target genre. Results show that it is indeed accurate, with results ranging from 85 to 77% precision and 40–61% recall, depending on how restrictive the application of the model is. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

SN Computer Science

ISSN

2662-995X

e-ISSN

—

Svazek periodika

5

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

1-17

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85206371953