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). We 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, we 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 our method: the “yellow light rule” and “fuel price” in China. Our work will help the development of TSA and its applications.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Web-Based Traffic Sentiment Analysis: Methods and Applications


    Contributors:
    Cao, Jianping (author) / Zeng, Ke (author) / Wang, Hui (author) / Cheng, Jiajun (author) / Qiao, Fengcai (author) / Wen, Ding (author) / Gao, Yanqing (author)


    Publication date :

    2014-04-01


    Size :

    1019914 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Sentiment Analysis of Arabic Tweets for Road Traffic Congestion and Event Detection

    Alomari, Ebtesam / Mehmood, Rashid / Katib, Iyad | Springer Verlag | 2019



    Sentiment analysis based product rating using textual reviews

    Sindhu, C / Vyas, Dyawanapally Veda / Pradyoth, Kommareddy | IEEE | 2017