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According to MTA [14], "convenience of stops" is one of the most important dimensions among all public transit satisfaction measurements.
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The author confirmed the significance of fare price in transit customer satisfaction.
Many researchers found that crowdedness has considerable influence on public transit customer satisfaction.
Wait and travel time are usually considered as critical measurements of transit customer satisfaction.
In this paper, we propose studying public transit customer satisfaction by analyzing online reviews and comments, which contain words expressing user sentiment or opinions about public transit service.
Recently, a variety of new data sources and an expanding set of novel analysis methods open up new opportunities for studying transit user satisfaction.
This research also provides an alternative method to collectively gather users' feedback and efficiently pre-process textual data related to transit customer satisfaction.
In the following sections, previous studies on public transit customer satisfaction evaluation are reviewed and the latent Dirichlet allocation (LDA) topic model is discussed.
This research serves as a pilot study to test the feasibility and reliability of using online review comments to investigate transit users' satisfaction dimensions.
These approaches have the potential to enhance model efficiency and effectiveness and will facilitate future model selection and modification to serve the emerging needs of transit customer satisfaction analysis.
Declining satisfaction levels among transit users lead to significant decrease in their customer loyalty regarding using transit again or recommending transit to a friend or relative.
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