Sentiment and Behavior Analysis of One Controversial American Individual on Twitter

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9948)


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?


Sentiment Analysis Presidential Candidate Twitter User Republican Party Positive Sentiment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank the CNPq, CAPES, and FAPESP (Proc. 2011/18496-7), for financial support.


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© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Instituto Nacional de Pesquisas Espaciais (INPE)São José dos CamposBrazil
  2. 2.Federal University of São Paulo (UNIFESP)São José dos CamposBrazil

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