This article analyzes Brazilian Consumers' Sentiments in a specific domain using a system, SentiMeter-Br. A Portuguese dictionary focused in a specific field of study was built, in which tenses and negative words are treated in a different way of other dictionaries, with a different metric. For the Portuguese dictionary performance validation, the results are compared with the SentiStrength algorithm and are evaluated by three Specialists in the field of study; each one analyzed 2000 texts captured from Twitter. Comparing the efficiency of the SentiMeter-Br and the SentiStrength against the Specialists' opinion, a Pearson correlation factor of 0.89 and 0.75 was reached, respectively. The polarity of the short texts were also tested through machine learning, with correctly classified instances of 71.79% by Sequential Minimal Optimization algorithm and F-Measure of 0.87 for positive and 0.91 for negative phrases. © 2013 IEEE.