Traffic Analysis Based on Short Texts from Social Media

摘要: Social networks provide information about activities of humans and social events. Thus, with the help networks, we can extract traffic events that occur in a city. In context an urban area, this kind data allows to obtaining contextual real-time shared among citizens will be useful address social, environmental economic issues. paper, authors describe methodology obtain related such as accidents or congestion, from Twitter messages RSS services. A text mining process is applied on acquire relevant data, then are classified by using machine learning algorithm. The geocoded transformed into geometric points represented map. final repository lets available for further works study area. As case consider Mexico City.