Comparing the Origin-Destination Matrices from Travel Demand Model and Social Media Data
In this paper the authors use Twitter data and a recently developed algorithm at the University of California Santa Barbara to extract Origin-Destination pairs in the Greater Los Angeles metropolitan area known as the Southern California Association of Governments (SCAG) region. This algorithm contains two steps: individual-based trajectory detection and place-based trip aggregation. In essence, if a person tweeted in different TAZs within 4 hours, it is considered to be one OD-trip. The extracted OD-trips were aggregated into 30 minute intervals. Then, the authors compare these trips with a traditional travel demand model (SCAG, 2012, 4-step model). Substantial spatial heterogeneity is found and a variety of social factors including the tweeting demographics. In this paper the authors illustrate the results from a spatially autoregressive regression model and a three-class latent class regression model that convert tweet derived trips to four-step trips accounting for zonal and trip-maker heterogeneity. In these regression models the authors use measures of business density and diversity, and population density as added explanatory/control variables, so that a unit contribution of a tweet trip can be adjusted by land-use effects and the trip producing zones in the twitter data can be explained in a more complete way. Preliminary results are encouraging and show the usefulness of harvested large-scale mobility data from location-based social media. The results also show the added value of latent class regression models in this experiment. The paper concludes with a review of next steps.
-
Supplemental Notes:
- This paper was sponsored by TRB committee ADB20 Standing Committee on Effects of Information and Communication Technologies (ICT) on Travel Choices. Alternate title: Can Twitter Data Be Used to Validate Travel Demand Models?
-
Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Lee, Jae Hyun
- Gao, Song
- Goulias, Konstadinos G
-
Conference:
- Transportation Research Board 95th Annual Meeting
- Location: Washington DC, United States
- Date: 2016-1-10 to 2016-1-14
- Date: 2016
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 24p
- Monograph Title: TRB 95th Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Algorithms; Origin and destination; Regression analysis; Social media; Traffic distribution; Travel demand
- Identifier Terms: Twitter
- Geographic Terms: Southern California
- Subject Areas: Data and Information Technology; Highways;
Filing Info
- Accession Number: 01594525
- Record Type: Publication
- Report/Paper Numbers: 16-0069
- Files: TRIS, TRB, ATRI
- Created Date: Mar 24 2016 10:51AM