Web-Based Traffic Sentiment Analysis: Methods and Applications

With the booming of social media, sentiment analysis has developed rapidly in recent years. However, only a few studies focused on the field of transportation, which failed to meet the stringent requirements of safety, efficiency, and information exchange of intelligent transportation systems (ITSs). The authors propose the traffic sentiment analysis (TSA) as a new tool to tackle this problem, which provides a new prospective for modern ITSs. Methods and models in TSA are proposed in this paper, and the advantages and disadvantages of rule- and learning-based approaches are analyzed based on web data. Practically, the authors applied the rule-based approach to deal with real problems, presented an architectural design, constructed related bases, demonstrated the process, and discussed the online data collection. Two cases were studied to demonstrate the efficiency of the method: the “yellow light rule” and “fuel price” in China. This work will help the development of TSA and its applications.

Language

  • English

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Filing Info

  • Accession Number: 01527810
  • Record Type: Publication
  • Files: TLIB, TRIS
  • Created Date: May 5 2014 11:56AM