Graduation Year


Document Type




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.


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.