In the last years researchers in the field of intelligent transportationsystems have made several efforts to extract valuable information from socialmedia streams. However, collecting domain-specific data from any social mediais a challenging task demanding appropriate and robust classification methods.In this work we focus on exploring geo-located tweets in order to create atravel-related tweet classifier using a combination of bag-of-words and wordembeddings. The resulting classification makes possible the identification ofinteresting spatio-temporal relations in S\~ao Paulo and Rio de Janeiro.
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