Data From: Social-Transportation Analytic Toolbox (STAT) for Transit Networks
Sponsor
This project was funded by the National Institute for Transportation and Communities (NITC). Funding was also provided by the University of Utah, Portland State University and the University of California at Riverside.
Document Type
Dataset
Publication Date
2019
Subjects
Local transit accessibility -- Evaluation, Twitter, Transportation -- Planning, Automatic data collection systems, Social media -- Applications to transportation planning
Abstract
This project builds an open-source, socio-transportation analytic (STAT) toolbox for public transit system planning in an effort to integrate social media and general transit feed specification (GTFS) data for transit agencies in evaluating and enhancing the performance of public transit systems. 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, 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 multidimensional objectives.
Rights
This work is marked with CC0 1.0 Universal
DOI
10.15760/TREC_datasets.04
Persistent Identifier
https://archives.pdx.edu/ds/psu/30335
Recommended Citation
Liu, Xiaoyue, Wei, Ran, Golub, Aaron, Wang, Liming. 2019. Data From:Social-Transportation Analytic Toolbox (STAT) for Transit Networks . NITC-RR-1080. Portland, OR: Transportation Research and Education Center (TREC). [Dataset]. https://doi.org/10.15760/TREC_datasets.04
Readme
portland watt.txt (8515 kB)
Portland Watt
salt lake city watt.txt (7759 kB)
Salt Lake City Watt
trimet_tweet_link_date.csv (3116 kB)
Trimet Tweets
uta_tweet_link_date.csv (3066 kB)
UTA Tweets
Description
The data supports the final report, NITC-RR-1080, Social-Transportation Analytic Toolbox (STAT) for Transit Networks - https://doi.org/10.15760/trec.229