Real time road traffic monitoring alert based on incremental learning from tweets

Social media has become an important source of near-instantaneous information about events and is increasingly also being analysed to provide predictive models, sentiment analysis and so on. One domain where social media data has value is transport and this paper looks at the exploitation of Twitter data in traffic management. A key issue is the identification and analysis of traffic-relevant content. A smart system is needed to identify traffic related tweets for traffic incident alerting. This paper proposes an instant traffic alert and warning system based on a novel LDA-based approach (“tweet-LDA”) for classification of traffic-related tweets. The system is evaluated and shown to perform better than related approaches.