Research Article Open Access

Block-Matching Twitter Data for Traffic Event Location

Amal Shuqair1 and Samuel Kozaitis1
  • 1 Florida Institute of Technology, United States
American Journal of Engineering and Applied Sciences
Volume 10 No. 2, 2017, 348-352

DOI: https://doi.org/10.3844/ajeassp.2017.348.352

Submitted On: 9 March 2017 Published On: 12 April 2017

How to Cite: Shuqair, A. & Kozaitis, S. (2017). Block-Matching Twitter Data for Traffic Event Location. American Journal of Engineering and Applied Sciences, 10(2), 348-352. https://doi.org/10.3844/ajeassp.2017.348.352

Abstract

We used a block-matching approach that is data-driven and relies mostly on patterns of tagged speech in Twitter streams as a way to identify events in road traffic. Events are useful because their location may identify the status of road segments, especially when cross-street data are available. Basing a system on patterns that are not pre-defined has the advantage of flexibility for a variety of scenarios.

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Keywords

  • Block-Matching
  • Parts of Speech
  • Social Media
  • Twitter