Social media analysis for traffic management

Given the data- and communication-intensive nature of developing transportation management systems, utilizing social media data provides a new route for dynamic collection of needs and experiences in a timely and direct fashion. In this research, we report the overall results of our retrospective analysis to explore how and to what extent social media data can support urban traffic management systems. We have conducted a mixed-method study, including both manual qualitative analysis, and automatic information extraction and natural language processing, on Twitter data. The results of our study show that although theoretical publications and books, in the context of traffic management systems, can help with the real-time traffic measurements, such as traffic flow and queue length, this is not sufficient to characterize context-sensitive aspects of these systems, which are crucial inputs in most of the real-time signal timing and traffic management methods.