Sentiment Analysis to support book selection: a study applied to the Skoob platform
DOI:
https://doi.org/10.5007/1518-2924.2022.e83588Abstract
Objective: This paper aims to apply the sentiment analysis technique to reviews published on the Skoob platform in order to propose a new evaluation parameter to help users in their decision-making about whether or not to read a book.
Methods: Exploratory research with a quantitative and qualitative approach, which used, to perform the sentiment analysis, the polarity detection technique, in order to automate the detection of the polarity degree of the opinions contained in the reviews, which can be positive, negative or neutral. A total of 45,114 reviews related to the 20 most read books among Skoob platform users were selected.
Results: The obtained results show the potential of applying sentiment analysis to the book reviews as another tool to help the Skoob platform user in his decision making about which book to start reading or which books to put on his list of next reads.
Conclusions: Book reviews are important inputs in a social network for readers, since they can influence the reading preferences of its users, as well as present the positive and negative characteristics of a given book. Applying Sentiment Analysis to the opinions contained in such reviews can provide indicators in an automated and fast way, making it possible to gauge users' behavior towards the books they have read, as well as being used as an alternative metric for book evaluation.
Downloads
References
ALMEIDA, R. J. A. LeIA - Léxico para Inferência Adaptada. 2018. Disponível em: https://github.com/rafjaa/LeIA. Acesso em: 04 dez. 2020.
BECKER, K.; TUMITAN, D. Introdução à mineração de opiniões: conceitos, aplicações e desafios. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS, 28., 2013, Recife. Anais […]. Porto Alegre: Sociedade Brasileira de Computação, 2013. p. 27-52.
BENEVENUTO, F.; RIBEIRO, F.; ARAÚJO, M. Métodos para análise de sentimentos em mídias sociais. In: SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB. MINICURSOS, 21., 2015, Manaus. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2015. p. 31-59.
CAMBRIA, E.; LIVINGSTONE, A.; HUSSAIN, A. The Hourglass of Emotions. In: ESPOSITO, A.; ESPOSITO, A. M.; VINCIARELLI, A.; HOFFMANN, R.; MÜLLER, V. C. (org.). Cognitive Behavioural Systems. Heidelberg: Springer, 2012. Disponível em: http://dx.doi.org/10.1007/978-3-642-34584-5_11. Acesso em: 30 jun. 2021.
CHIAVETTA, F.; BOSCO, G. L.; PILATO, G. A lexicon-based approach for sentiment classification of Amazon books reviews in Italian language. In: INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND TECHNOLOGIES, 12., 2016, Rome. Proceedings […]. Rome: INSTICC, 2016. p. 159–170.
GOODFELLOW, I.; BENGIO, Y.; COURVILLE, A. Deep Learning. Cambridge: MIT Press, 2016. Disponível em: http://www.deeplearningbook.org. Acesso em: 25 jun. 2021.
HUTTO, C.; GILBERT, E. Vader: A parsimonious rule-based model for sentiment analysis of social media text. In: PROCEEDINGS OF THE INTERNATIONAL AAAI CONFERENCE ON WEB AND SOCIAL MEDIA, 8., 2014, Ann Arbor. Proceedings […]. Palo Alto: AAAI, 2014. p. 216–225.
HOTHO, A.; NÜRNBERGER, A.; PAAß, G. A brief survey of text mining. LDV Forum, Trier, v. 20, n. 1, p. 19-62, 2005.
LIU, B. Sentiment analysis and subjectivity. Handbook of natural language processing, v. 2, n. 2010, p. 627-666, 2010.
NASCIMENTO, A. G.; ODDONE, N. E. Métricas alternativas para a avaliação da produção científica: a altmetria e seu uso pelos bibliotecários. In: ENCONTRO NACIONAL DE PESQUISA EM CIÊNCIA DA INFORMAÇÃO, 17., 2016, Salvador. Anais [...]. Salvador: ANCIB, 2016. p. 3071-3085.
PANG, B.; LEE, L. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, Delft, v. 2, n. 1-2, p. 1-94, 2008.
PÅLSSON, A.; SZERSZEN, D. Sentiment Classification in Social Media: An Analysis of Methods and the Impact of Emoticon Removal. 2016. Disponível em: https://www.diva-portal.org/smash/get/diva2:930520/FULLTEXT01.pdf. Acesso em: 16 jun. 2021.
PAK, A.; PAROUBEK, P. Twitter as a corpus for sentiment analysis and opinion mining. In: INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 7., 2010, Valletta. Proceedings […]. Paris: ELRA, 2010. p. 1320-1326.
PIRYANI, R.; GUPTA, V.; SINGH, V. K.; PINTO, D. Book impact assessment: A quantitative and text-based exploratory analysis. Journal of Intelligent & Fuzzy Systems, Amsterdam, v.34, n. 6, p. 1–10, 2018.
RAJU, B. N.; NAIKODI, C.; SURESH, L. Sentiment analysis of product attribute using social media. International Journal of Engineering Research, Bengaluru, v. 5, n. 4, p. 808-813, 2016.
SKOOB. Plataforma de Rede Social para Leitores. Disponível em: https://www.skoob.com.br. Acesso em: 08 dez. 2020.
WANG, K.; LIU, X.; HAN, Y. Exploring Goodreads reviews for book impact assessment. Journal of Informetrics, Amsterdam, v. 13, n. 3, p. 874–886, 2019.
ZHOU, Q.; ZHANG, C.; ZHAO, S. X.; CHEN, B. Measuring book impact based on the multi-granularity online review mining. Scientometrics, Amsterdam, v. 107, n. 3, p. 1–21, 2016.
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Ronnie Shida Marinho, Clayton Martins Pereira, José Eduardo Santarem Segundo

This work is licensed under a Creative Commons Attribution 4.0 International License.
The author must guarantee that:
- there is full consensus among all the coauthors in approving the final version of the document and its submission for publication.
- the work is original, and when the work and/or words from other people were used, they were properly acknowledged.
Plagiarism in all of its forms constitutes an unethical publication behavior and is unacceptable. Encontros Bibli has the right to use software or any other method of plagiarism detection.
All manuscripts submitted to Encontros Bibli go through plagiarism and self-plagiarism identification. Plagiarism identified during the evaluation process will result in the filing of the submission. In case plagiarism is identified in a manuscript published in the journal, the Editor-in-Chief will conduct a preliminary investigation and, if necessary, will make a retraction.
This journal, following the recommendations of the Open Source movement, provides full open access to its content. By doing this, the authors keep all of their rights allowing Encontros Bibli to publish and make its articles available to the whole community.
Encontros Bibli content is licensed under a Creative Commons Attribution 4.0 International License.
Any user has the right to:
- Share - copy, download, print or redistribute the material in any medium or format.
- Adapt - remix, transform and build upon the material for any purpose, even commercially.
According to the following terms:
- Attribution - You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything that the license permits.


















