Twitter Data Can Improve Event Planning, Subway Operations
Preliminary study finds tweets effective for gathering real-time passenger information.
Data from Twitter and other social media platform can be used to improve event planning, route scheduling, crowd regulations and other subway operations, according to engineers conducting a preliminary study.
“Social media offers a cost-effective way to obtain real-time data on monitoring subway passenger flow,” says Qing He, Stephen Still Assistant Professor in Transportation Engineering and Logistics at University at Buffalo, and the study’s corresponding author.
“Our results show that data from apps like Twitter can help public transportation officials prepare for and react to passenger surges during concerts, baseball games and other big events,” he added.
In addition to Qing, who has appointments in the university’s Department of Civil, Structural and Environmental Engineering and the Department of Industrial and Systems Engineering, the study was co-authored by Ph.D. student Jing Gao, an assistant professor in the UB’s Department Computer Science and Engineering, and Ming Ni, a Ph.D. fellow from the UB’s Department of Industrial and Systems Engineering.
To conduct the study, the researchers gathered subway ridership information from April to October in 2014 via turnstiles at Mets-Willets Point station in Queens, New York. They chose the station because it’s located next to Citi Field, the home of Major League Baseball’s New York Mets, and the USTA Billie Jean King National Tennis Center, where the U.S. Open tennis championships are held each year.
The researchers also collected nearly 30 million tweets geotagged to the New York City area during the same time. They then filtered the tweets by their geographic coordinates (a feature that Twitter users enable on their accounts), the context of the tweet, the time and other pertinent elements.
Using six different computer models, the researchers then analyzed the data and found what they describe as a moderate positive correlation between passenger flow and the rates of tweets during big events.
“The results are encouraging for two reasons. First, they indicate that increases in social media posts and subway ridership can be linked. Secondly, we have developed a method to track this correlation,” says Gao. “Now, the challenge is to refine this method so it can be used by public transit system operators to improve their systems.”