Tell me how you write and I'll tell you what you read: a study on the writing style of book reviews

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AYDB2IBVN" target="_blank" >RIV/00216208:11320/25:YDB2IBVN - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162196949&doi=10.1108%2fJD-04-2023-0073&partnerID=40&md5=80ecc2a29fb1bb3bbcf687fc45af3ce7" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162196949&doi=10.1108%2fJD-04-2023-0073&partnerID=40&md5=80ecc2a29fb1bb3bbcf687fc45af3ce7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1108/JD-04-2023-0073" target="_blank" >10.1108/JD-04-2023-0073</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Tell me how you write and I'll tell you what you read: a study on the writing style of book reviews

Popis výsledku v původním jazyce

Purpose: The authors’ goal is to investigate variations in the writing style of book reviews published on different social reading platforms and referring to books of different genres, which enables acquiring insights into communication strategies adopted by readers to share their reading experiences. Design/methodology/approach: The authors propose a corpus-based study focused on the analysis of A Good Review, a novel corpus of online book reviews written in Italian, posted on Amazon and Goodreads, and covering six literary fiction genres. The authors rely on stylometric analysis to explore the linguistic properties and lexicon of reviews and the authors conducted automatic classification experiments using multiple approaches and feature configurations to predict either the review's platform or the literary genre. Findings: The analysis of user-generated reviews demonstrates that language is a quite variable dimension across reading platforms, but not as much across book genres. The classification experiments revealed that features modelling the syntactic structure of the sentence are reliable proxies for discerning Amazon and Goodreads reviews, whereas lexical information showed a higher predictive role for automatically discriminating the genre. Originality/value: The high availability of cultural products makes information services necessary to help users navigate these resources and acquire information from unstructured data. This study contributes to a better understanding of the linguistic characteristics of user-generated book reviews, which can support the development of linguistically-informed recommendation services. Additionally, the authors release a novel corpus of online book reviews meant to support the reproducibility and advancements of the research. © 2023, Emerald Publishing Limited.

Název v anglickém jazyce

Tell me how you write and I'll tell you what you read: a study on the writing style of book reviews

Popis výsledku anglicky

Purpose: The authors’ goal is to investigate variations in the writing style of book reviews published on different social reading platforms and referring to books of different genres, which enables acquiring insights into communication strategies adopted by readers to share their reading experiences. Design/methodology/approach: The authors propose a corpus-based study focused on the analysis of A Good Review, a novel corpus of online book reviews written in Italian, posted on Amazon and Goodreads, and covering six literary fiction genres. The authors rely on stylometric analysis to explore the linguistic properties and lexicon of reviews and the authors conducted automatic classification experiments using multiple approaches and feature configurations to predict either the review's platform or the literary genre. Findings: The analysis of user-generated reviews demonstrates that language is a quite variable dimension across reading platforms, but not as much across book genres. The classification experiments revealed that features modelling the syntactic structure of the sentence are reliable proxies for discerning Amazon and Goodreads reviews, whereas lexical information showed a higher predictive role for automatically discriminating the genre. Originality/value: The high availability of cultural products makes information services necessary to help users navigate these resources and acquire information from unstructured data. This study contributes to a better understanding of the linguistic characteristics of user-generated book reviews, which can support the development of linguistically-informed recommendation services. Additionally, the authors release a novel corpus of online book reviews meant to support the reproducibility and advancements of the research. © 2023, Emerald Publishing Limited.

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

Journal of Documentation

ISSN

0022-0418

e-ISSN

—

Svazek periodika

80

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

23

Strana od-do

180-202

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85162196949