In the last years researchers in the field of intelligent transportation systems have made several efforts to extract valuable information from social media streams. However, collecting domain-specific data from any social media is a challenging task demanding appropriate and robust classification methods. In this work we focus on exploring geo-located tweets in order to create a travel-related tweet classifier using a combination of bag-of-words and word embeddings. The resulting classification makes possible the identification of interesting spatio-temporal relations in São Paulo and Rio de Janeiro.
CITATION STYLE
Pereira, J., Pasquali, A., Saleiro, P., & Rossetti, R. (2017). Transportation in social media: An automatic classifier for travel-related tweets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10423 LNAI, pp. 355–366). Springer Verlag. https://doi.org/10.1007/978-3-319-65340-2_30
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