United States Department of Transportation
i
Real-Time Transportation Social Media Analytics Using Pulse (Pulse-T)
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2021-08-01
[PDF-1.00 MB]
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Edition:Final Report (2020 – 2021)
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Abstract:As city planners and transportation system planners consider changes and upgrades to transportation systems and infrastructure, they require models that accurately reflect communities’ needs. Planners need access to advanced activity-travel demand analysis models that are responsive and sensitive to emerging transportation technologies; models are needed that not only provide insights into communities’ current travel demands and behaviors, but also help understand people’s attitudes and expectations toward a change — or a proposed change — in a community’s transportation infrastructure or transportation options. These models often rely on data collected from surveys or opinion polls. Surveys result in regimented answers to specific questions, only measure behavior at a single-point in time, and are often vulnerable to self-selection bias. These limitations prevent attitudes from being observed across the population and across time, thus hindering the ability to do real-time analysis and get the most accurate and recent public sentiment to inform policy decisions. In this project, Arizona State University’s Decision Theater (DT) staff built PULSE-T to address these limitations. PULSE-T gathers data directly from Twitter, allowing for information to be gathered live about the impact of a policy change. Twitter offers a large volume of publicly available data in which people and groups broadcast their feelings and preferences far more widely than what a survey instrument could capture.
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