A Novel Transit Riders' Satisfaction Metric: Riders' Sentiments Measured from Online Social Media Data

The goal of this paper is to use an emerging data source, Twitter, and conduct sentiment analysis to evaluate transit riders' satisfaction. Transit authorities have access to vast amounts of performance metrics that measure ridership, timeliness, efficiency, safety, cleanliness, and service to name a few. These performance metrics, however, are generally one-sided; they represent the interests of the business and are not customer based. This paper recognizes the limitations of standard performance metrics and attempts to gauge transit riders' sentiment by measuring Twitter feeds. Sentiment analysis software is used to classify a population of rider's sentiment over a period of time. Conclusions are drawn from totals of positive and negative sentiment, normalized average sentiment, and the total number of Tweets collected over a time period.