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Utilizing Social Media Data for Estimating Transit Performance Metrics in A Pre- and Post-Covid-19 World
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2023-09-01
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[PDF-3.67 MB]
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Edition:Final report, 3/1/22-9/30/23
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Abstract:This study explores the benefits of text and sentiment analysis of Twitter data, as well as the applications of such analysis towards understanding customer sentiment, transit performance, and the relationship between the two. Ultimately the objective of this research is to determine which performance metrics customers most frequently mention and are most passionate about, and where these sentiments are directed when riding with Metropolitan Transportation Authority New York City Transit and how these compare and contrast to the performance indicators reported by the agency. This is carried out by analyzing a year’s worth of Twitter data collected from users mentioning their transit experience and recognizing trends regarding sentiment. These trends are then compared with the data reported by MTA in order to find a correlation. The results show that customers mostly tweet negative experiences over positive experiences found with service and are most frequently critical about wait time and delays.
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