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Title: Twitter or Chatter? Involving Social Media Data Analysis in Traffic Incident Management
Accession Number: 01628063
Record Type: Component
Abstract: The contents posted by users on social media sites generate large volumes of data. The feasibility of using social media data, specifically from Twitter, for detecting traffic incidents is evaluated. For the purpose of incident management, a text-mining process is presented to extract and search real-time traffic-related Twitter data by two methods, keywords search and specific users search. The presented framework consists of three main components, Twitter data mining, location extraction and traffic management. The approach is implemented using data from the Chicago area; using on-line simulation-based traffic estimation and prediction tools, traffic management strategies developed to reduce the impact of incidents are evaluated. The results confirm the potential of Twitter posts to complement and improve the effectiveness of dynamic traffic management approaches for incident conditions.
Supplemental Notes: This paper was sponsored by TRB committee AHB20 Standing Committee on Freeway Operations.
Monograph Title: Monograph Accession #: 01618707
Report/Paper Numbers: 17-02328
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Pagination: 20p
Publication Date: 2017
Conference:
Transportation Research Board 96th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References; Tables
TRT Terms: Identifier Terms: Uncontrolled Terms: Geographic Terms: Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management
Source Data: Transportation Research Board Annual Meeting 2017 Paper #17-02328
Files: TRIS, TRB, ATRI
Created Date: Dec 8 2016 10:52AM
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0000-0002-8443-8928