@InCollection{OliveiraCotSerSanQui:2016:SeBeAn,
               author = "Oliveira, Jo{\~a}o Eliakin Mota de and Cotacallapa Choque, Frank 
                         Moshe and Seron, Wilson and Santos, Rafael Duarte Coelho dos and 
                         Quiles, Marcos G.",
                title = "Sentiment and behavior analysis of one controversial american 
                         individual on twitter",
            booktitle = "Neural information processing",
            publisher = "Springer Verlag",
                 year = "2016",
               editor = "Ozawa, S. and Ikeda, K. and Liu, D. and Hirose, A. and Doya, K. 
                         and Lee, M.",
                pages = "509--518",
             keywords = "Artificial intelligence, Information science, Learning systems, 
                         Social networking (online) Behavior analysis, Interesting points, 
                         Machine learning techniques, Opinion formation, Sentiment 
                         analysis, Social media, Temporal Data, Temporal pattern.",
             abstract = "Social media is a convenient tool for expressing ideas and a 
                         powerful means for opinion formation. In this paper, we apply 
                         sentiment analysis and machine learning techniques to study a 
                         controversial American individual on Twitter., aiming to grasp 
                         temporal patterns of opinion changes and the geographical 
                         distribution of sentiments (positive, neutral or negative), in the 
                         American territory. Specifically, we choose the American TV 
                         presenter and candidate for the Republican party nomination, 
                         Donald J. Trump. The results acquired aim to elucidate some 
                         interesting points about the data, such as: what is the 
                         distribution of users considering a match between their sentiment 
                         and their relevance? Which clusters can we get from the temporal 
                         data of each state? How is the distribution of sentiments, before 
                         and after, the first two Republican party debates?.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         de S{\~a}o Paulo (UNIFESP)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Federal de S{\~a}o Paulo 
                         (UNIFESP)}",
                  doi = "10.1007/978-3-319-46672-9_57",
                  url = "http://dx.doi.org/10.1007/978-3-319-46672-9_57",
                 isbn = "978-331946671-2",
             language = "en",
          seriestitle = "Lecture Notes in Computer Science (LNCS)",
               volume = "9948",
        urlaccessdate = "27 abr. 2024"
}