# Transportation in Social Media: an automatic classifier for travel-related tweets

## TL;DR

This paper presents an automatic classifier for travel-related tweets using a combination of bag-of-words and word embeddings, enabling the extraction of spatio-temporal travel patterns from geo-located social media data in Brazilian cities.

## Contribution

It introduces a novel classification approach combining bag-of-words and word embeddings for travel-related tweets, facilitating transportation analysis from social media streams.

## Key findings

- Effective classification of travel-related tweets achieved
- Identified spatio-temporal travel patterns in São Paulo and Rio de Janeiro
- Demonstrated robustness of the method in social media data

## Abstract

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 S\~ao Paulo and Rio de Janeiro.