Social-Transportation Analytic Toolbox (STAT) for Transit Networks

Xiaoyue Liu, University of Utah


  • Ran Wei, University of California, Riverside
  • Aaron Golub, Portland State University
  • Liming Wang, Portland State University


The new Social-Transportation Analytic Toolbox (STAT) for Transit Networks, developed by NITC researchers in a multi-university collaboration, is a dynamic platform that combines Twitter, general transit feed specification (GTFS), and census transportation planning products (CTPP)—in this case,  job density data—to help agencies evaluate overall system performance and identify connectivity gaps. It can also act as a decision support tool for recommending service improvements. The STAT is an open-source, publicly accessible toolbox with three components: 
1. Temporal distribution of transit stops’ average travel times, 
2. Transit stop positioning in Google Maps with geomapped tweets around that stop, and 
3. Overall transit access visualization at the TAZ (traffic analysis zone) level.

This toolbox is novel and essential to transit agencies in two aspects. First, it enables the integration, analysis and visualization of two major new open transportation data sources—social media and GTFS data—to support transit decision making. Second, it allows transit agencies to evaluate service network efficiency and access equity of transit systems in a cohesive manner, and identify areas for improvement to better achieve these multi-dimensional objectives. Two transit agencies, the Utah Transit Authority (UTA) and TriMet, worked with the research team to evaluate the usability of the toolbox.


The STAT system will assist agencies in evaluating the overall system performance and identifying existing public transit connectivity/accessibility gap. It can also act as a decision support tool for recommending improvements (e.g., prioritize the stations and routes, identify the necessity for introducing a new line within existing infrastructure, etc.) by jointly considering the input from social media. In addition to serving transit agency staff, the tool can be used in university curriculum and by advocacy organizations engaged in transportation decision-making. Finally, the project lays the foundation for NITC developing other open-source tools using big data.

Project Details

Project Type:
Project Status:
End Date:
June 15,2019
UTC Grant Cycle:
NITC 16 Initial Projects
UTC Funding:

Other Products

  • Social-Transportation Analytic Toolbox (STAT) for Transit Networks (PRESENTATION)
  • Dai Z, Liu XC, Chen Z, Guo R, Ma X. A predictive headway-based bus-holding strategy with dynamic control point selection: A cooperative game theory approach. Transportation Research Part B: Methodological. 2019 Jul 1;125:29-51. (PUBLICATION)
  • Chen Z, Liu XC, Wei R. Agent-based approach to analyzing the effects of dynamic ridesharing in a multimodal network. Computers, Environment and Urban Systems. 2019 Mar 1;74:126-35. (PUBLICATION)
  • Haghighi, N. N., Liu, X. C., Wei, R., Li, W. W., & Shao, H. (2018). Using Twitter data for transit performance assessment: a framework for evaluating transit riders' opinions about quality of service. Public Transport, 10(2), 363-377. (PUBLICATION)
  • Social-Transportation Analytic Toolbox (STAT) (WEBSITE)