Detecting Events and Sentiment on Twitter for Improving Urban Mobility

  title={Detecting Events and Sentiment on Twitter for Improving Urban Mobility},
  author={Antonio Candelieri and Francesco Archetti},
The streams of tweets from and to the Twitter account of urban transport operators have been considered. A computational module has been designed and developed in order to collect tweets and, on the fly, analyze them to detect some relevant event (e.g. accidents, sudden traffic jams, service interruption, etc.) and/or evaluate possible sentiments and opinions about the quality of service. Events are recognized through a simple word matching while sentiment analysis is performed via supervised… CONTINUE READING

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