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.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Mining Transportation Information from Social Media for Planned and Unplanned Events


    Contributors:
    Z. Zhang (author) / M. Ni (author) / Q. He (author) / S. Still (author) / J. Gao (author)

    Publication date :

    2016


    Size :

    68 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




    Cognitive load during planned and unplanned virtual shopping:Evidence from a neurophysiological perspective

    Kakaria, Shobhit / Saffari, Farzad / Zoëga Ramsøy, Thomas et al. | BASE | 2023

    Free access

    From unplanned to planned agricultural use: making an asset out of wastewater

    Lier, J. B. / Huibers, F. P. | British Library Online Contents | 2010


    Methodology to Evaluate Unplanned Proposed Transportation Projects

    M. M. Smith / L. A. Hoel / J. S. Miller | NTIS | 2008



    Short-Term Metro Ridership Prediction During Unplanned Events

    Zhao, Yangyang / Ma, Zhenliang / Jiang, Xinguo et al. | Transportation Research Record | 2021