Exploring Brazilian Cultural Identity Through Reading Preferences
Resumo
In Brazil, each region has its own cultural identity regarding accent, gastronomy, customs, all of which may reflect in its literature. Specially, we believe that country's background and contextual features are directly related to what people read. Hence, we perform a cross-state comparison analysis based on Brazilian reading preferences through a multipartite network model. Also, we explore the effects of socioeconomic and demographic factors on favorite books and writing genres. Such cross-state analyses highlight how the country is culturally rich, where each region has its own distinctive culture. Our findings offer great opportunities for the Brazilian book industry by enhancing current knowledge on social indicators related to reading preferences.
Palavras-chave:
cultural analysis, Brazilian culture, reading preferences, multipartite networks, books
Referências
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Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press.
Digiampietri, L. et al. (2014). Análise da rede dos doutores que atuam em computação no brasil. In BraSNAM, pages 33–44.
Fredrickson, M.M. and Chen, Y. (2019). Permutation and randomization tests for network analysis. Social Networks, 59:171–183.
Krackardt, D. (1987). Qap partialling as a test of spuriousness. Social networks, 9(2):171–186.
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Lance, G. N. and Williams, W. T. (1967). Mixed-data classificatory programs i - agglomerative systems. Australian Computer Journal, 1(1):15–20.
Liu, M. et al. (2018). The relation of culture, socio-economics, and friendship to music preferences: A large-scale, cross-country study. PloS one, 13(12):e0208186.
Maity, S. K. et al. (2017). Book reading behavior on goodreads can predict the amazon best sellers. In ASONAM, pages 451–454.
Mondelli, M. L. B. et al. (2018). O que os países escutam: Analisando a rede de gêneros musicais ao redor do mundo. In BraSNAM. SBC.
Nascimento, M. L. et al. (2018). Uma análise do fator cultural em tecnologias persuasivas: um estudo de caso da rede social facebook. In BraSNAM. SBC.
Sabri, N. et al. (2020). A cross-country study on cultural similarities based on book preferences. Soc. Netw. Anal. Min., 10(1):86.
Serrano, M. A´ . et al. (2009). Extracting the multiscale backbone of complex weighted networks. Proceedings of the National Academy of Sciences, 106(16):6483–6488.
Shahsavari, S. et al. (2020). An automated pipeline for character and relationship extraction from readers literary book reviews on goodreads.com. In WebSci, pages 277–286.
Silva, M. O., Scotfield, C., Oliveira, G. P., Seufitelli, D. B., and Moro, M. M. (2021). BraCID: Brazilian Cultural Identity Information Through Reading Preferences.
Simpson, W. (2001). Qap: The quadratic assignment procedure. North American Stata Users’ Group Meetings 2001 1.2.
Wang, K. et al. (2019). Exploring goodreads reviews for book impact assessment. J. Informetrics, 13(3):874–886.
Yucesoy, B., Wang, X., Huang, J., and Barab´asi, A. (2018). Success in books: a big data approach to bestsellers. EPJ Data Sci., 7(1):7.
Zhao, Y. et al. (2021). Do cultural differences affect users’ e-learning adoption? A metaanalysis. Br. J. Educ. Technol., 52(1):20–41.
Borges de Souza, T. R. C. et al. (2015). Brazilian cultural differences and their effects on the web interfaces user experience. In Int’l Conf Cross-Cultural Design Methods, Practice and Impact, pages 209–220.
Butts, C. T. (2020). sna: Tools for Social Network Analysis. R package version 2.6.
Choi, J. H. et al. (2006). Comparing world city networks: a network analysis of internet backbone and air transport intercity linkages. Global Networks, 6(1):81–99.
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press.
Digiampietri, L. et al. (2014). Análise da rede dos doutores que atuam em computação no brasil. In BraSNAM, pages 33–44.
Fredrickson, M.M. and Chen, Y. (2019). Permutation and randomization tests for network analysis. Social Networks, 59:171–183.
Krackardt, D. (1987). Qap partialling as a test of spuriousness. Social networks, 9(2):171–186.
Lance, G. N. andWilliams,W. T. (1966). Computer Programs for Hierarchical Polythetic Classification (“Similarity Analyses”). The Computer Journal, 9(1):60–64.
Lance, G. N. and Williams, W. T. (1967). Mixed-data classificatory programs i - agglomerative systems. Australian Computer Journal, 1(1):15–20.
Liu, M. et al. (2018). The relation of culture, socio-economics, and friendship to music preferences: A large-scale, cross-country study. PloS one, 13(12):e0208186.
Maity, S. K. et al. (2017). Book reading behavior on goodreads can predict the amazon best sellers. In ASONAM, pages 451–454.
Mondelli, M. L. B. et al. (2018). O que os países escutam: Analisando a rede de gêneros musicais ao redor do mundo. In BraSNAM. SBC.
Nascimento, M. L. et al. (2018). Uma análise do fator cultural em tecnologias persuasivas: um estudo de caso da rede social facebook. In BraSNAM. SBC.
Sabri, N. et al. (2020). A cross-country study on cultural similarities based on book preferences. Soc. Netw. Anal. Min., 10(1):86.
Serrano, M. A´ . et al. (2009). Extracting the multiscale backbone of complex weighted networks. Proceedings of the National Academy of Sciences, 106(16):6483–6488.
Shahsavari, S. et al. (2020). An automated pipeline for character and relationship extraction from readers literary book reviews on goodreads.com. In WebSci, pages 277–286.
Silva, M. O., Scotfield, C., Oliveira, G. P., Seufitelli, D. B., and Moro, M. M. (2021). BraCID: Brazilian Cultural Identity Information Through Reading Preferences.
Simpson, W. (2001). Qap: The quadratic assignment procedure. North American Stata Users’ Group Meetings 2001 1.2.
Wang, K. et al. (2019). Exploring goodreads reviews for book impact assessment. J. Informetrics, 13(3):874–886.
Yucesoy, B., Wang, X., Huang, J., and Barab´asi, A. (2018). Success in books: a big data approach to bestsellers. EPJ Data Sci., 7(1):7.
Zhao, Y. et al. (2021). Do cultural differences affect users’ e-learning adoption? A metaanalysis. Br. J. Educ. Technol., 52(1):20–41.
Publicado
18/07/2021
Como Citar
SILVA, Mariana O.; SCOFIELD, Clarisse; OLIVEIRA, Gabriel P.; SEUFITELLI, Danilo B.; MORO, Mirella M..
Exploring Brazilian Cultural Identity Through Reading Preferences. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 10. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 115-126.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2021.16130.
