Mining Transportation Information from Social Media for Planned and Unplanned Events

The objective of this project is on mining social media data to deduce useful traveler’s information with a special emphasis under events, including both planned events (such as sporting games), and unplanned events (such as traffic accidents). Specifically, the project proposes to develop effective and efficient techniques to collect, extract and mine social media data to support advanced traveler information systems and traffic operators. By mining social media based semantics, especially text semantics, this project aims to achieve the following aims: 1) Forecast transit ridership under large sporting games; 2) Identify causality between abnormal traffic flow pattern and social media data; 2) Detect traffic accident using online social media data and traffic loop-detector data.

  • Record URL:
  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:

    Transportation Informatics University Transportation Center

    University at Buffalo
    223 Ketter Hall
    Buffalo, NY  United States  14260

    Research and Innovative Technology Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Zhang, Zhenhua
    • Ni, Ming
    • He, Qing
    • Gao, Jing
  • Publication Date: 2016-5-1

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; References; Tables;
  • Pagination: 68p

Subject/Index Terms

Filing Info

  • Accession Number: 01600748
  • Record Type: Publication
  • Contract Numbers: DTRT13-G-UTC48
  • Files: UTC, NTL, TRIS, RITA, ATRI, USDOT
  • Created Date: May 24 2016 1:54PM