Um olhar sobre turismo gastronômico: um caso no TripAdvisor
Resumo
Analisar e extrair informac ̧oes do Conte ̃ udo Gerado pelo Usuário (UGC) tornou-se um topico de pesquisa com crescente atenção. Esses dados contem informações como opiniões dos consumidores, classificações e recomendações de produtos e serviços, sendo uma rica fonte de informação para auxiliar nas decisoes de compras. Muitos artigos foram publicados sobre UGC relacionado ao turismo, em especial, o turismo gastronomico. No entanto, ao observar a literatura, verificou-se a escassez de antecedentes que abordem a analise de avaliaçoe online de restaurantes brasileiros. Nesse sentido, o foco deste trabalho e preencher essa lacuna por meio de um estudo de caso da cidade de Santarem. Os resultados mostram que os profissionais desse segmento podem utilizar essas analises a fim de aprimorarem a experiência de seus serviços.
Palavras-chave:
User-Generated Content
Referências
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da Silva, M. B. d. O., de Souza Moreira, M. C., de Souza, Á. G. R., de Oliveira Aruda, D., and Mariani, M. A. P. (2019). Gastronomia no tripadvisor: O que os turistas comentam sobre os restaurantes de bonito-ms? gastronomy on tripadvisor: What tourists comment about restaurants in bonito-ms-brazil? ROSA DOS VENTOS-Turismo e Hospitalidade, 11(4).
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G1 (2019). Turismo em Santarém cresce em 2018 e injeta R$ 176 milhões na ecomia, aponta estudo. Disponı́vel em: https://g1.globo.com/pa/santare m-regiao/noticia/2019/02/11/turismo-em-santarem-cresce-e m-2018-e-injeta-r-176-milhoes -na-economia-aponta-estudo.ghtml. Acesso em: 23 de Abril de 2020.
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Schmunk, S., Höpken, W., Fuchs, M., and Lexhagen, M. (2013). Sentiment analysis: Extracting decision-relevant knowledge from ugc. In Information and Communication Technologies in Tourism 2014, pages 253–265. Springer.
Silva, W., Santana, Á., Lobato, F., and Pinheiro, M. (2017). A Methodology for Comunity Detection in Twitter. In Proceedings of the International Conference on Web Intelligence, pages 1006–1009.
Silva Junior, J., Rossi, R., and Lobato, F. (2020). Uma abordagem baseada em letras para a descoberta de conhecimento da música brasileira: o sertanejo como um estudo de caso. In Anais do XVI Encontro Nacional de Inteligência Artificial e Computacional, pages 949–960, Porto Alegre, RS, Brasil. SBC.
Silveira, M. P., Xavier, W. Z., and Marques-Neto, H. T. (2018). Análises de dados de sistemas crowdsourcing: estudo de caso de avaliações de estabelecimentos realizadas no yelp. In Anais do VII Brazilian Workshop on Social Network Analysis and Mining. SBC.
Taecharungroj, V. and Mathayomchan, B. (2019). Analysing tripadvisor reviews of tourist attractions in phuket, thailand. Tourism Management, 75:550–568.
Talib, R., Hanif, M. K., Ayesha, S., and Fatima, F. (2016). Text mining: techniques, applications and issues. International Journal of Advanced Computer Science and Applications, 7(11):414–418.
Valdivia, A., Hrabova, E., Chaturvedi, I., Luzón, M. V., Troiano, L., Cambria, E., and Herrera, F. (2019). Inconsistencies on tripadvisor reviews: A unified index between users and sentiment analysis methods. Neurocomputing, 353:3–16.
Vijayarani, S., Ilamathi, M. J., and Nithya, M. (2015). Preprocessing techniques for text mining-an overview. International Journal of Computer Science & Communication Networks, 5(1):7–16.
Xiang, Z. and Gretzel, U. (2010). Role of social media in online travel information search. Tourism management, 31(2):179–188.
Yan, L., Cha, N., Cho, H., and Hwang, J. (2019). Video diffusion in user-generated content website: An empirical analysis of bilibili. In 2019 21st International Conference on Advanced Communication Technology (ICACT), pages 81–84. IEEE.
Zhao, Y. (2012). R and data mining: Examples and case studies. Academic Press.
Almeida, G. R., Guimarães, I., Jacob Jr, A. F. L., and Lobato, F. M. F. (2020). Fontes de dados gerados por usuários: quais plataformas considerar? In Anais do IX Brazilian Workshop on Social Network Analysis and Mining, pages 25–36. SBC.
Ashish, D. and Duggal, S. (2015). Evaluation of websites using Balanced Scorecard (BSC) Approach in the Hotel Landscape in India. Journal of Tourism, 16(1):1–16.
Chen, Y. and Skiena, S. (2014). Building sentiment lexicons for all major languages. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 383–389.
Chen, Y., Zhang, H., Liu, R., Ye, Z., and Lin, J. (2019). Experimental explorations on short text topic mining between lda and nmf based schemes. Knowledge-Based Systems, 163:1–13.
Chen, Z., Mukherjee, A., Liu, B., Hsu, M., Castellanos, M., and Ghosh, R. (2013). Leveraging multi-domain prior knowledge in topic models. In Twenty-Third International Joint Conference on Artificial Intelligence.
Cirqueira, D., Pinheiro, M. F., Jacob, A., Lobato, F., and Santana, Á. (2018). A literature review in preprocessing for sentiment analysis for brazilian portuguese social media. In 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pages 746–749. IEEE.
da Silva, M. B. d. O., de Souza Moreira, M. C., de Souza, Á. G. R., de Oliveira Aruda, D., and Mariani, M. A. P. (2019). Gastronomia no tripadvisor: O que os turistas comentam sobre os restaurantes de bonito-ms? gastronomy on tripadvisor: What tourists comment about restaurants in bonito-ms-brazil? ROSA DOS VENTOS-Turismo e Hospitalidade, 11(4).
de Sousa, G. N., Almeida, G. R., and Lobato, F. (2019). Social Network Advertising Classification Based on Content Categories. In International Conference on Business Information Systems, pages 396–404.
Freitas, A. A. (2014). Comprehensible classification models: a position paper. ACM SIGKDD explorations newsletter, 15(1):1–10.
G1 (2019). Turismo em Santarém cresce em 2018 e injeta R$ 176 milhões na ecomia, aponta estudo. Disponı́vel em: https://g1.globo.com/pa/santare m-regiao/noticia/2019/02/11/turismo-em-santarem-cresce-e m-2018-e-injeta-r-176-milhoes -na-economia-aponta-estudo.ghtml. Acesso em: 23 de Abril de 2020.
He, W., Zha, S., and Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33(3):464–472.
Lee, S., Ro, H., et al. (2016). The impact of online reviews on attitude changes: the differential effects of review attributes and consumer knowledge. International Journal of Hospitality Management, 56:1–9.
Lobato, F., Pinheiro, M., Jacob, A., Reinhold, O., and Santana, Á. (2016). Social crm: Biggest challenges to make it work in the real world. In International Conference on Business Information Systems, pages 221–232. Springer.
Marcolin, C., Becker, J. L., Wild, F., Schiavi, G., and Behr, A. (2019). Business analytics in tourism: Uncovering knowledge from crowds. BAR-Brazilian Administration Review, 16(2).
Narangajavana Kaosiri, Y., Callarisa Fiol, L. J., Moliner Tena, M. A., Rodriguez Artola, R. M., and Sanchez Garcia, J. (2019). User-generated content sources in social media: A new approach to explore tourist satisfaction. Journal of Travel Research, 58(2):253– 265.
Navı́o-Marco, J., Ruiz-Gómez, L. M., and Sevilla-Sevilla, C. (2018). Progress in formation technology and tourism management: 30 years on and 20 years after the internet-revisiting buhalis & law’s landmark study about etourism. Tourism Management, 69:460–470.
Nistoreanu, B. G., Nicodim, L., and Diaconescu, D. M. (2018). Gastronomic tourismstages and evolution. In Proceedings of the International Conference on Business Excellence, volume 12, pages 711–717. Sciendo.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.
Rodrigues, L., Junior, A., and Lobato, F. (2020). Notı́cias relacionadas a pessoas com deficiência: uma análise do conteúdo gerado pelos usuários em postagens de mı́dias sociais. In Anais do XVI Encontro Nacional de Inteligência Artificial e Computacional, pages 811–822. SBC.
Santos, G., Santos, M., Mota, V. F., Benevenuto, F., and Silva, T. H. (2018). Neutral or negative? sentiment evaluation in reviews of hosting services. In Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, pages 347–354.
Schmunk, S., Höpken, W., Fuchs, M., and Lexhagen, M. (2013). Sentiment analysis: Extracting decision-relevant knowledge from ugc. In Information and Communication Technologies in Tourism 2014, pages 253–265. Springer.
Silva, W., Santana, Á., Lobato, F., and Pinheiro, M. (2017). A Methodology for Comunity Detection in Twitter. In Proceedings of the International Conference on Web Intelligence, pages 1006–1009.
Silva Junior, J., Rossi, R., and Lobato, F. (2020). Uma abordagem baseada em letras para a descoberta de conhecimento da música brasileira: o sertanejo como um estudo de caso. In Anais do XVI Encontro Nacional de Inteligência Artificial e Computacional, pages 949–960, Porto Alegre, RS, Brasil. SBC.
Silveira, M. P., Xavier, W. Z., and Marques-Neto, H. T. (2018). Análises de dados de sistemas crowdsourcing: estudo de caso de avaliações de estabelecimentos realizadas no yelp. In Anais do VII Brazilian Workshop on Social Network Analysis and Mining. SBC.
Taecharungroj, V. and Mathayomchan, B. (2019). Analysing tripadvisor reviews of tourist attractions in phuket, thailand. Tourism Management, 75:550–568.
Talib, R., Hanif, M. K., Ayesha, S., and Fatima, F. (2016). Text mining: techniques, applications and issues. International Journal of Advanced Computer Science and Applications, 7(11):414–418.
Valdivia, A., Hrabova, E., Chaturvedi, I., Luzón, M. V., Troiano, L., Cambria, E., and Herrera, F. (2019). Inconsistencies on tripadvisor reviews: A unified index between users and sentiment analysis methods. Neurocomputing, 353:3–16.
Vijayarani, S., Ilamathi, M. J., and Nithya, M. (2015). Preprocessing techniques for text mining-an overview. International Journal of Computer Science & Communication Networks, 5(1):7–16.
Xiang, Z. and Gretzel, U. (2010). Role of social media in online travel information search. Tourism management, 31(2):179–188.
Yan, L., Cha, N., Cho, H., and Hwang, J. (2019). Video diffusion in user-generated content website: An empirical analysis of bilibili. In 2019 21st International Conference on Advanced Communication Technology (ICACT), pages 81–84. IEEE.
Zhao, Y. (2012). R and data mining: Examples and case studies. Academic Press.
Publicado
20/10/2020
Como Citar
F. JUNIOR, Luiz; SILVA JUNIOR, Jorge; LOBATO, Fábio.
Um olhar sobre turismo gastronômico: um caso no TripAdvisor. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 17. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 519-530.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2020.12156.
