Graduation Year
2022
Document Type
Thesis
Degree
M.S.
Degree Name
Master of Science (M.S.)
Degree Granting Department
Civil and Environmental Engineering
Major Professor
Yu Zhang, Ph.D.
Committee Member
Fred Mannering, Ph.D.
Committee Member
Qing Lu, Ph.D.
Committee Member
Pei-Sung Lin, Ph.D.
Keywords
EVTOL, Natural Language Process, Sentiment Analysis, UAM, Vertiport
Abstract
Urban Air Mobility (UAM) is a wide concept that will enable access to on-demand air mobility, cargo delivery, medical applications, and emergency services that is run through a connected and integrated transportation system. This study aims to investigate social media data to compare the major topics discussed in the United States and rest of the world and perform a sentiment analysis to see if the comments are positive, negative, or neutral. Twitter was the primary source of information that was used in this thesis, as it is a place where people interact, create, and share information and ideas online. In this thesis I used an analytical approach to analyze the social media information within the context of social network theory and used the sentiment expressed in the content as a proxy to measure the performance. Text mining techniques and machine learning algorithms were employed to examine the social media information, to collect tweets using certain keywords, and do a comparison study between the United States and Rest of the World.
Scholar Commons Citation
Tahmid, S M Toki, "Comparison Study of Consumer’s Perception toward Urban Air Mobility in the United States and Rest of the World Using Social Media Information" (2022). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/9820
