01593358

Component

https://doi.org/10.3141/2553-10

Social media receive increasing attention as a crowdsourced information resource in traffic operations and management. Tweets, which are blogged and shared by great masses of people, may be associated with some major social activities. In this study these tweets are called "Twitter concentrations." The public activities behind Twitter concentrations potentially pose more pressure on the traffic network and cause traffic surges within a specified time and location. However, it is still unknown how closely the Twitter concentrations and traffic surges are correlated. This study fuses a set of tweets and traffic data collected during 2014 in Northern Virginia and investigates the correlation between Twitter concentrations and traffic surges in July. The results show the promise and effectiveness of the proposed methods and even provide insights into the causality of nonrecurrent traffic surges.

01588890

16-3203

English

pp 90–98

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309441155

Print

Figures (7) ; References (32) ; Tables (3)

Cluster analysis; Detection and identification systems; Methodology; Social media; Traffic congestion; Traffic forecasting

Twitter

Northern Virginia

Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting

TRIS, TRB, ATRI

Jan 12 2016 5:25PM

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