StarRest: Um Conjunto de Dados de Restaurantes Estrelados e respectivas Avaliações
Resumo
O artigo apresenta o StarRest, um conjunto de dados abrangente sobre restaurantes brasileiros estrelados pelo Guia Michelin, incluindo comentários de clientes coletados entre 2008 e 2024 em seis plataformas de avaliação online. A análise destaca a popularidade das plataformas, a distribuição de comentários por idioma e a atividade dos clientes, revelando uma distribuição de longa cauda na participação. São discutidas possíveis aplicações do conjunto de dados, como análise de sentimentos, tendências gastronômicas e desenvolvimento de recomendações personalizadas, além de desafios encontrados na coleta e organização dos dados.
Palavras-chave:
Restaurante, Plataformas de Avaliação, Análise de Sentimentos
Referências
de Melo, T. (2024). Dataset StarRest. Mendeley Data. [link], versão 1.
Gan, Q., Ferns, B. H., Yu, Y., and Jin, L. (2017). A text mining and multidimensional sentiment analysis of online restaurant reviews. Journal of Quality Assurance in Hospitality & Tourism, 18(4):465–492.
Gavilan, D., Avello, M., and Martinez-Navarro, G. (2018). The influence of online ratings and reviews on hotel booking consideration. Tourism Management, 66:53–61.
Guo, X., Pesonen, J., and Komppula, R. (2021). Comparing online travel review platforms as destination image information agents. Information Technology & Tourism, 23:159–187.
Hu, Y., Hu, C., Tran, T., Kasturi, T., Joseph, E., and Gillingham, M. (2021). What’s in a name?–gender classification of names with character based machine learning models. Data Mining and Knowledge Discovery, 35(4):1537–1563.
Melo, T. (2024). Estudo exploratório do setor gastronômico brasileiro: Uma análise de dados de plataformas online. In Anais do XIII Brazilian Workshop on Social Network Analysis and Mining, pages 200–206, Porto Alegre, RS, Brasil. SBC.
Panyakham, P. (2024). A comparison of the performance of google translate in 2018 and 2023. Journal of Liberal Arts Prince of Songkla University, 16(1):271938–271938.
Piller, C. (1999). Everyone is a critic in cyberspace. Los Angeles Times, 3(12):A1.
Rodríguez-López, M. E., Alcántara-Pilar, J. M., Del Barrio-García, S., and Muñoz-Leiva, F. (2020). A review of restaurant research in the last two decades: A bibliometric analysis. International Journal of Hospitality Management, 87:102387.
Taecharungroj, V. and Mathayomchan, B. (2019). Analysing tripadvisor reviews of tourist attractions in phuket, thailand. Tourism Management, 75:550–568.
Yu, C.-E. and Zhang, X. (2020). The embedded feelings in local gastronomy: a sentiment analysis of online reviews. Journal of Hospitality and Tourism Technology, 11(3):461–478.
Gan, Q., Ferns, B. H., Yu, Y., and Jin, L. (2017). A text mining and multidimensional sentiment analysis of online restaurant reviews. Journal of Quality Assurance in Hospitality & Tourism, 18(4):465–492.
Gavilan, D., Avello, M., and Martinez-Navarro, G. (2018). The influence of online ratings and reviews on hotel booking consideration. Tourism Management, 66:53–61.
Guo, X., Pesonen, J., and Komppula, R. (2021). Comparing online travel review platforms as destination image information agents. Information Technology & Tourism, 23:159–187.
Hu, Y., Hu, C., Tran, T., Kasturi, T., Joseph, E., and Gillingham, M. (2021). What’s in a name?–gender classification of names with character based machine learning models. Data Mining and Knowledge Discovery, 35(4):1537–1563.
Melo, T. (2024). Estudo exploratório do setor gastronômico brasileiro: Uma análise de dados de plataformas online. In Anais do XIII Brazilian Workshop on Social Network Analysis and Mining, pages 200–206, Porto Alegre, RS, Brasil. SBC.
Panyakham, P. (2024). A comparison of the performance of google translate in 2018 and 2023. Journal of Liberal Arts Prince of Songkla University, 16(1):271938–271938.
Piller, C. (1999). Everyone is a critic in cyberspace. Los Angeles Times, 3(12):A1.
Rodríguez-López, M. E., Alcántara-Pilar, J. M., Del Barrio-García, S., and Muñoz-Leiva, F. (2020). A review of restaurant research in the last two decades: A bibliometric analysis. International Journal of Hospitality Management, 87:102387.
Taecharungroj, V. and Mathayomchan, B. (2019). Analysing tripadvisor reviews of tourist attractions in phuket, thailand. Tourism Management, 75:550–568.
Yu, C.-E. and Zhang, X. (2020). The embedded feelings in local gastronomy: a sentiment analysis of online reviews. Journal of Hospitality and Tourism Technology, 11(3):461–478.
Publicado
14/10/2024
Como Citar
DE MELO, Tiago.
StarRest: Um Conjunto de Dados de Restaurantes Estrelados e respectivas Avaliações. In: DATASET SHOWCASE WORKSHOP (DSW), 6. , 2024, Florianópolis/SC.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 114-124.
DOI: https://doi.org/10.5753/dsw.2024.241893.
