In the last decade, sentiment analysis (SA), also known as opinion mining, has attracted an increasing interest. It is a hard challenge for language technologies, and achieving good results is much more difficult than some people think. The task of automatically classifying a text written in a natural language into a positive or negative feeling, opinion or subjectivity (Pang and Lee, 2008), is sometimes so complicated that even different human annotators disagree on the classification to be assigned to a given text. Personal interpretation by an individual is different from others, and this is also affected by cultural factors and each person’s experience. And the shorter the text, and the worse written, the more difficult the task becomes, as in the case of messages on social networks like Twitter or Facebook.