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

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Journal of Documentation

  • ISSN

    0022-0418

  • e-ISSN

  • Volume of the periodical

    80

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    23

  • Pages from-to

    180-202

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85162196949