2022
DOI: 10.1007/978-3-030-98305-5_18
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Book Genre Classification Based on Reviews of Portuguese-Language Literature

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Cited by 3 publications
(5 citation statements)
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“…Even so, the number of works considering content in other languages is increasing. The Portuguese language is widely spoken in the world, with over 230 million native speakers, 1 and NLP methods have been used for several applications using Portuguese-language content, including regional reading preferences discovery [Silva et al 2021a], detection of loanwords [Muhongo et al 2022], and genre classification [Scofield et al 2022].…”
Section: Related Workmentioning
confidence: 99%
“…Even so, the number of works considering content in other languages is increasing. The Portuguese language is widely spoken in the world, with over 230 million native speakers, 1 and NLP methods have been used for several applications using Portuguese-language content, including regional reading preferences discovery [Silva et al 2021a], detection of loanwords [Muhongo et al 2022], and genre classification [Scofield et al 2022].…”
Section: Related Workmentioning
confidence: 99%
“…This work presents the initial part of our research. We develop further studies using the dataset and methodology presented here, such as book genre classification with online reviews [10].…”
Section: Contributionsmentioning
confidence: 99%
“…[10] ClarisseScofield et al, 2022. Book Genre Classification Based on Reviews of Portuguese-Language Literature.…”
mentioning
confidence: 99%
“…The insights that such reviews provide into readers' opinions are commonly exploited by publishers and authors for understanding the preferences of their readers (Aerts et al ., 2017; Dimitrov et al ., 2015; Maity et al ., 2019; Thelwall, 2019; Wang et al ., 2019). Among these studies, we notice that still little is known about the diverse communication strategies adopted by readers to share their reading experiences with others in terms of stylistic variations between reviews written across different platforms or referring to books belonging to different genres (Hajibayova, 2019; Rebora et al ., 2021; Scofield et al ., 2022), especially when it comes to book reviews written in Italian. However, the analysis of stylistic variations of reviewers' writing style can contribute useful perspectives to information behaviour research, especially in the context of DSR practices.…”
Section: Introductionmentioning
confidence: 99%
“…Less attention has been paid to exploiting user-generated reviews written by readers. To the best of our knowledge, the main exception is Saraswat (2022), which used Amazon book reviews for genre classification using recurrent neural networks, and the study conducted by Scofield et al . (2022), which relied on multiple machine learning algorithms to categorize 24 fiction genres starting from a collection of 325 Portuguese book reviews posted on Goodreads.…”
Section: Introductionmentioning
confidence: 99%