Abstract Online user-generated content provides a valuable source for identifying dimensions of services. This study proposes a framework for extracting the dimensions of consumer satisfaction of public transportation services using unsupervised latent Dirichlet allocation model. A pilot study was performed on 17,747 online user reviews collected from 1452 public transportation agencies (including streetcar, light rail, heavy rail, boat, and aerial tram) in the United States over 8 years. The proposed approach is able to identify a few dimensions that were not discussed in the previous literature. This research also provides an alternative method to collectively gather users’ feedback and efficiently pre-process textual data related to transit customer satisfaction.


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    Title :

    Public Transit Customer Satisfaction Dimensions Discovery from Online Reviews


    Contributors:
    Gao, Lu (author) / Yu, Yao (author) / Liang, Wuling (author)

    Published in:

    Urban Rail Transit ; 2 , 3 ; 146-152


    Publication date :

    2016-10-11


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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