Master of Science (M.S.)
Degree Granting Department
Civil and Environmental Engineering
Yu Zhang, Ph.D.
Fred Mannering, Ph.D.
Qing Lu, Ph.D.
Pei-Sung Lin, Ph.D.
EVTOL, Natural Language Process, Sentiment Analysis, UAM, Vertiport
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.