Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 81–84 (2020)
Abstract. Analyzing User-Generated Content present in social media has become mandatory for companies looking for maintaining competitiveness. These data contain information such as consumer opinions, and recommendations that are seen as rich sources of information for the development of decision support systems. When observing the state of the art, it was found that there is a lack of antecedents that address the analysis of online reviews of Brazilian restaurants. In this sense, the focus of this work is to fill this gap through a case study of Santar\'em city. The results show that professionals in this segment can use these analyzes in order to improve the user's experiences and increase their profits.
- G1, “Turismo em Santarém cresce em 2018 e injeta R$ 176 milhões na economia, aponta estudo,” https://g1.globo.com/pa/santarem-regiao/noticia/2019/02/11/turismo-em-santarem-cresce-em-2018-e-injeta-r-176-milhoes-na-economia-aponta-estudo.ghtml. Accessed 21 April 2020., 2019.
- J. Navío-Marco, L. M. Ruiz-Gómez, and C. Sevilla-Sevilla, “Progress in information technology and tourism management: 30 years on and 20 years after the internet-revisiting buhalis & law’s landmark study about etourism,” Tourism Management, vol. 69, 2018. https://doi.org/10.1016/j.tourman.2018.06.002
- Y. Narangajavana Kaosiri, L. J. Callarisa Fiol, M. A. Moliner Tena, R. M. Rodriguez Artola, and J. Sanchez Garcia, “User-generated content sources in social media: A new approach to explore tourist satisfaction,” Journal of Travel Research, vol. 58, no. 2, 2019. https://doi.org/10.1177/0047287517746014
- A. J. Kim and K. K. Johnson, “Power of consumers using social media: Examining the influences of brand-related user-generated content on facebook,” Computers in Human Behavior, vol. 58, 2016. https://doi.org/10.1016/j.chb.2015.12.047
- S. Lee, H. Ro et al., “The impact of online reviews on attitude changes: the differential effects of review attributes and consumer knowledge.” International Journal of Hospitality Management, vol. 56, 2016. https://doi.org/10.1016/j.ijhm.2016.04.004
- S. Schmunk, W. Höpken, M. Fuchs, and M. Lexhagen, “Sentiment analysis: Extracting decision-relevant knowledge from ugc,” in Information and Communication Technologies in Tourism 2014. Springer, 2013, https://doi.org/10.1007/978-3-319-03973-2_19.
- B. G. Nistoreanu, L. Nicodim, and D. M. Diaconescu, “Gastronomic tourism-stages and evolution,” in Proceedings of the International Conference on Business Excellence, vol. 12, no. 1. Sciendo, 2018. https://doi.org/10.2478/picbe-2018-0063
- G. J. Miller, “Comparative analysis of big data analytics and bi projects,” in 2018 Federated Conference on Computer Science and Information Systems (FedCSIS). IEEE, 2018. http://dx.doi.org/10.15439/2018F125
- A. Klein, M. Riekert, and V. Dinev, “Accurate retrieval of corporate rep-utation from online media using machine learning,” in 2019 Federated Conference on Computer Science and Information Systems (FedCSIS). IEEE, 2019. http://dx.doi.org/10.15439/2019F169
- R. Talib, M. K. Hanif, S. Ayesha, and F. Fatima, “Text mining: techniques, applications and issues,” International Journal of Advanced Computer Science and Applications, vol. 7, no. 11, 2016. https://doi.org/10.14569/IJACSA.2016.071153
- Y. Zhao, R and Data Mining: Examples and Case Studies, 12 2012. ISBN 978-0-12-396963-7
- F. Lobato, M. Pinheiro, A. Jacob, O. Reinhold, and Á. Santana, “Social crm: Biggest challenges to make it work in the real world,” in International Conference on Business Information Systems. Springer, 2016. https://doi.org/10.1007/978-3-319-52464-1_20
- L. Yan, N. Cha, H. Cho, and J. Hwang, “Video diffusion in user-generated content website: An empirical analysis of bilibili,” in 2019 21st International Conference on Advanced Communication Technology (ICACT). IEEE, 2019. https://doi.org/10.23919/ICACT.2019. 8701897
- C. Marcolin, J. L. Becker, F. Wild, G. Schiavi, and A. Behr, “Business analytics in tourism: Uncovering knowledge from crowds,” BAR-Brazilian Administration Review, vol. 16, no. 2, 2019. https://doi.org/10.5748/9788599693148-15CONTECSI/PS-5707
- G. Santos, M. Santos, V. F. Mota, F. Benevenuto, and T. H. Silva, “Neutral or negative? sentiment evaluation in reviews of hosting services,” in Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, 2018. https://doi.org/10.1145/3243082.3243091
- V. Taecharungroj and B. Mathayomchan, “Analysing tripadvisor reviews of tourist attractions in phuket, thailand,” Tourism Management, vol. 75, 2019. https://doi.org/10.1016/j.tourman.2019.06.020
- M. P. Silveira, W. Z. Xavier, and H. T. Marques-Neto, “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, 2018. https://doi.org/10.5753/brasnam.2018.3593
- T. B. F. Martins, C. M. Ghiraldelo, M. d. G. V. Nunes, and O. N. de Oliveira Junior, “Readability formulas applied to textbooks in brazilian portuguese,” 1996.
- B. Fang, Q. Ye, D. Kucukusta, and R. Law, “Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics,” Tourism Management, vol. 52, 2016. https://doi.org/10.1016/j.tourman.2015.07.018
- D. Cirqueira, M. F. Pinheiro, A. Jacob, F. Lobato, and Á. Santana, “A literature review in preprocessing for sentiment analysis for brazilian portuguese social media,” in 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 2018. https://doi.org/10.1109/WI.2018.00008
- N. Rodríguez-Barroso, A. R. Moya, J. A. Fernández, E. Romero, E. Martínez-Cámara, and F. Herrera, “Deep learning hyper-parameter tuning for sentiment analysis in twitter based on evolutionary algorithms,” in 2019 Federated Conference on Computer Science and Information Systems (FedCSIS). IEEE, 2019. http://dx.doi.org/10.15439/2019F183
- Y. Chen and S. Skiena, “Building sentiment lexicons for all major languages,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2014, pp. 383–389.
- L. Rodrigues, A. Junior, and F. Lobato, “Disability-Related News: An Analysis of User-Generated Content on Social Media Posts,” in In Proceedings of the 16th National Meeting on Artificial and Computational Intelligence. SBC, 2020. https://doi.org/10.5753/eniac.2019.9336
- Y. Chen, H. Zhang, R. Liu, Z. Ye, and J. Lin, “Experimental explorations on short text topic mining between lda and nmf based schemes,” Knowledge-Based Systems, vol. 163, 2019. https://doi.org/10.1016/j.knosys.2018.08.011
- J. Silva Junior, R. Rossi, and F. Lobato, “A Lyric-Based Approach for Brazilian Music Knowledge Discovery: Brazilian Country Music as a Case Study,” in In Proceedings of the 16th National Meeting on Artificial and Computational Intelligence. SBC, 2020. https://doi.org/10.5753/eniac.2019.9348
- Z. Chen, A. Mukherjee, B. Liu, M. Hsu, M. Castellanos, and R. Ghosh, “Leveraging multi-domain prior knowledge in topic models,” in Twenty-Third International Joint Conference on Artificial Intelligence, 2013.