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Abstract: This thesis utilized Twitter data to determine if people's sentiment had connections to the travel mode choice they made. Whether the Transit Oriented Development (TOD), with catchment radius of 2 kilometer and 0.5 mile, boosts people's sentiment toward non-vehicle travel modes was also assessed. Moreover, a model was built to predict vehicle usage rate in transit sheds using a Artificial ... read moreNeural Network (ANN). The result tells the association between people's sentiment toward travel modes and people's travel behavior was very weak (R2 < 0.03). People's overall sentiment is statistically significant to people's travel mode usage. The models effectively predicted the vehicle usage rate in the transit sheds and they gave us accuracy scores larger than 0.87. This thesis utilized social media to provide another angle to understand people's travel behavior. Also, with the models planners and developers can effectively predict one TOD areas' vehicle usage rate and develop better policies.
Thesis (M.S.)--Tufts University, 2018.
Submitted to the Dept. of Urban and Environmental Policy and Planning.
Advisor: Justin Hollander.
Committee: Sumeeta Srinivasan.
Keywords: Urban planning, Transportation, and Psychology.read less