Institute of Transportation, MOTC

Title	Sensing Daily Travel Satisfaction Of Commuters by Mining Social Media
Year	2018
Degree	Master
School	Institute of Transportation Science, Tamkang University
Author
Summary	This study aims at proposing a generalized process of social media mining and sentiment analysis to sense commuters’ daily travel satisfaction. Firstly, available social media websites are chosen to perform text mining and filtered text database related to daily travel topics by using crawler systems. Secondly, a sentiment analysis is conducted to propose a multiple emotion recognition model which can be used to sense commuters’ emotions about public transportation vehicles including high speed rail, commuter rail, mass rapid transit, urban bus, intercity bus, specific bus and taxi by using Convolutional Neural Networks (CNN) algorithm from deep learning. Thirdly, an empirical study is performed to validate commuters’ daily travel satisfaction towards different public transportation vehicles with a five-grade-scale emotion recognition survey. Finally, influence factors depicting interrelationships among critical topics concerned public transportation services in social media mining are clustered with K-means algorithm and corresponding strategies to improve negative emotions against certain public transportation services are also provided. Empirical results show that the precision percentage of proposed model to verify critical variables of commuter’s public transportation satisfaction approximates 79% under five-grade scales. Either commuter or commercial trip purpose arrivals at destinations on time are much concerned by public transportation commuters. Driver behavior and timetable are also valued by public transportation commuters. It is recommended that operators should pay more attention to adjusting timetable and conducting systematical driver training programs for better emotions. In addition, fare topic is not significant for public transportation commuters that means current fare structures of public transportation are relatively acceptable by commuters. The proposed generalized process of social media mining and sentiment analysis in this study can be expanded with adequate modifications or improvements to grasp real-time information about net citizens’ emotion trends for decision makers.
Hashtags