What Makes a Book Successful? A Study on Portuguese-language Literature
Resumo
Analyzing the success of books is a matter of interest among publishers, professional book reviewers, expert writers, and even curious readers. Such a task has many influencing factors concerning the intrinsic content and quality of the book (e.g., interest, novelty, writing style, and engaging plot) and others regarding external factors such as social context, author relationships, and luck for publication. Faced with so many variables, recognizing a successful literary work is a challenging endeavor even for specialists in the publishing market. Our objective is: to explore a dataset of books in the Portuguese language created to obtain more knowledge about the different variables of success in the literary context; to understand and evaluate the metrics collected that indicate new perceptions about books using graphical views.
Palavras-chave:
Portuguese literature, success analysis, web data, data visualization
Referências
Vikas Ganjigunte Ashok et al. 2013. Success with style: Using writing style to predict the success of novels. In Proceedings of the 2013 conference on empirical methods in natural language processing. 1753–1764.
Judith A. Chevalier and Dina Mayzlin. 2006. The Effect of Word of Mouth on Sales: Online Book Reviews. Journal of Marketing Research 43, 3 (2006), 345–354. https://doi.org/10.1509/jmkr.43.3.345
Michel Clement, Dennis Proppe, and Armin Rott. 2007. Do critics make best-sellers? Opinion leaders and the success of books. Journal of Media Economics 20, 2 (2007), 77–105. https://doi.org/10.1080/08997760701193720
Alain d’Astous et al. 2006. Factors influencing readers’ interest in new book releases: An experimental study. Poetics 34, 2 (2006), 134–147. https://doi.org/10.1016/j.poetic.2005.12.001
Suraj Maharjan et al. 2018. A Genre-Aware Attention Model to Improve the Likability Prediction of Books. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. ACL, 3381–3391. https://doi.org/10.18653/v1/d18-1375
Suraj Maharjan et al. 2018. Letting Emotions Flow: Success Prediction by Modeling the Flow of Emotions in Books. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). Association for Computational Linguistics, New Orleans, Louisiana, 259–265. https://doi.org/10.18653/v1/N18-2042
Miguel V. Oliveira and Tiago de Melo. 2020. Investigating sets of linguistic features for two sentiment analysis tasks in Brazilian Portuguese web reviews. In Anais Estendidos do XXVI Simpósio Brasileiro de Sistemas Multimídia e Web. SBC, 45–48. https://doi.org/10.5753/webmedia_estendido.2020.13060
Denilson Alves Pereira. 2021. A survey of sentiment analysis in the Portuguese language. Artificial Intelligence Review 54, 2 (01 Feb 2021), 1087–1115. https://doi.org/10.1007/s10462-020-09870-1
Christina Schmidt-Stölting, Eva Blömeke, and Michel Clement. 2011. Success drivers of fiction books: An empirical analysis of hardcover and paperback editions in Germany. Journal of Media Economics 24, 1 (2011), 24–47.
Clarisse Scofield, Mariana O. Silva, Luiza de Melo-Gomes, and Mirella M. Moro. 2022. Book Genre Classification Based on Reviews of Portuguese-Language Literature. In Computational Processing of the Portuguese Language: 15th International Conference, PROPOR (Fortaleza, Brazil). 188–197. https://doi.org/10.1007/978-3-030-98305-5_18
Silva et al. 2021. An Improved NER Methodology to the Portuguese Language. Mobile Networks and Applications 26, 1 (01 Feb 2021), 319–325. https://doi.org/10.1007/s11036-020-01644-x
Mariana Silva, Clarisse Scofield, Gabriel Oliveira, Danilo Seufitelli, and Mirella Moro. 2021. Exploring Brazilian Cultural Identity Through Reading Preferences. In Anais do X Brazilian Workshop on Social Network Analysis and Mining (Evento Online). SBC, Porto Alegre, RS, Brasil, 115–126. https://doi.org/10.5753/brasnam.2021.16130
Mariana O. Silva, Clarisse Scofield, and Mirella Moro. 2021. PPORTAL: Public Domain Portuguese-language Literature Dataset. In DSW. SBC, Porto Alegre, RS, Brasil, 77–88. https://doi.org/10.5753/dsw.2021.17416
Mariana O. Silva, Clarisse Scofield, and Mirella M. Moro. 2021. PPORTAL: Public domain Portuguese-language literature Dataset. https://doi.org/10.5281/zenodo.5178063
Xindi Wang et al. 2019. Success in books: predicting book sales before publication. EPJ Data Science 8, 1 (17 Oct 2019), 31. https://doi.org/10.1140/epjds/s13688-019-0208-6
Burcu Yucesoy et al. 2018. Success in books: a big data approach to bestsellers. EPJ Data Science 7, 1 (06 Apr 2018), 7. https://doi.org/10.1140/epjds/s13688-018-0135-y
Zhou et al. [n. d.]. Measuring book impact based on the multi-granularity online review mining. Scientometrics 107, 3 ([n. d.]), 1435–1455. https://doi.org/10.1007/s11192-016-1930-5
Judith A. Chevalier and Dina Mayzlin. 2006. The Effect of Word of Mouth on Sales: Online Book Reviews. Journal of Marketing Research 43, 3 (2006), 345–354. https://doi.org/10.1509/jmkr.43.3.345
Michel Clement, Dennis Proppe, and Armin Rott. 2007. Do critics make best-sellers? Opinion leaders and the success of books. Journal of Media Economics 20, 2 (2007), 77–105. https://doi.org/10.1080/08997760701193720
Alain d’Astous et al. 2006. Factors influencing readers’ interest in new book releases: An experimental study. Poetics 34, 2 (2006), 134–147. https://doi.org/10.1016/j.poetic.2005.12.001
Suraj Maharjan et al. 2018. A Genre-Aware Attention Model to Improve the Likability Prediction of Books. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. ACL, 3381–3391. https://doi.org/10.18653/v1/d18-1375
Suraj Maharjan et al. 2018. Letting Emotions Flow: Success Prediction by Modeling the Flow of Emotions in Books. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). Association for Computational Linguistics, New Orleans, Louisiana, 259–265. https://doi.org/10.18653/v1/N18-2042
Miguel V. Oliveira and Tiago de Melo. 2020. Investigating sets of linguistic features for two sentiment analysis tasks in Brazilian Portuguese web reviews. In Anais Estendidos do XXVI Simpósio Brasileiro de Sistemas Multimídia e Web. SBC, 45–48. https://doi.org/10.5753/webmedia_estendido.2020.13060
Denilson Alves Pereira. 2021. A survey of sentiment analysis in the Portuguese language. Artificial Intelligence Review 54, 2 (01 Feb 2021), 1087–1115. https://doi.org/10.1007/s10462-020-09870-1
Christina Schmidt-Stölting, Eva Blömeke, and Michel Clement. 2011. Success drivers of fiction books: An empirical analysis of hardcover and paperback editions in Germany. Journal of Media Economics 24, 1 (2011), 24–47.
Clarisse Scofield, Mariana O. Silva, Luiza de Melo-Gomes, and Mirella M. Moro. 2022. Book Genre Classification Based on Reviews of Portuguese-Language Literature. In Computational Processing of the Portuguese Language: 15th International Conference, PROPOR (Fortaleza, Brazil). 188–197. https://doi.org/10.1007/978-3-030-98305-5_18
Silva et al. 2021. An Improved NER Methodology to the Portuguese Language. Mobile Networks and Applications 26, 1 (01 Feb 2021), 319–325. https://doi.org/10.1007/s11036-020-01644-x
Mariana Silva, Clarisse Scofield, Gabriel Oliveira, Danilo Seufitelli, and Mirella Moro. 2021. Exploring Brazilian Cultural Identity Through Reading Preferences. In Anais do X Brazilian Workshop on Social Network Analysis and Mining (Evento Online). SBC, Porto Alegre, RS, Brasil, 115–126. https://doi.org/10.5753/brasnam.2021.16130
Mariana O. Silva, Clarisse Scofield, and Mirella Moro. 2021. PPORTAL: Public Domain Portuguese-language Literature Dataset. In DSW. SBC, Porto Alegre, RS, Brasil, 77–88. https://doi.org/10.5753/dsw.2021.17416
Mariana O. Silva, Clarisse Scofield, and Mirella M. Moro. 2021. PPORTAL: Public domain Portuguese-language literature Dataset. https://doi.org/10.5281/zenodo.5178063
Xindi Wang et al. 2019. Success in books: predicting book sales before publication. EPJ Data Science 8, 1 (17 Oct 2019), 31. https://doi.org/10.1140/epjds/s13688-019-0208-6
Burcu Yucesoy et al. 2018. Success in books: a big data approach to bestsellers. EPJ Data Science 7, 1 (06 Apr 2018), 7. https://doi.org/10.1140/epjds/s13688-018-0135-y
Zhou et al. [n. d.]. Measuring book impact based on the multi-granularity online review mining. Scientometrics 107, 3 ([n. d.]), 1435–1455. https://doi.org/10.1007/s11192-016-1930-5
Publicado
07/11/2022
Como Citar
SCOFIELD, Clarisse; SILVA, Mariana O.; MORO, Mirella M..
What Makes a Book Successful? A Study on Portuguese-language Literature. In: CONCURSO DE TRABALHOS DE INICIAÇÃO CIENTÍFICA - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 28. , 2022, Curitiba.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 69-72.
ISSN 2596-1683.
DOI: https://doi.org/10.5753/webmedia_estendido.2022.227042.
