  The enormous amount of texts published daily by Internet users has fostered
the development of methods to analyze this content in several natural language
processing areas, such as sentiment analysis. The main goal of this task is to
classify the polarity of a message. Even though many approaches have been
proposed for sentiment analysis, some of the most successful ones rely on the
availability of large annotated corpus, which is an expensive and
time-consuming process. In recent years, distant supervision has been used to
obtain larger datasets. So, inspired by these techniques, in this paper we
extend such approaches to incorporate popular graphic symbols used in
electronic messages, the emojis, in order to create a large sentiment corpus
for Portuguese. Trained on almost one million tweets, several models were
tested in both same domain and cross-domain corpora. Our methods obtained very
competitive results in five annotated corpora from mixed domains (Twitter and
product reviews), which proves the domain-independent property of such
approach. In addition, our results suggest that the combination of emoticons
and emojis is able to properly capture the sentiment of a message.
