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Twitter to Model Traffic Flows
Can Twitter data be used to understand and explain travel patterns? What is the relationship between commuting and non-commuting trips? Local and regional planners struggle to keep up with rapid changes in mobility patterns, but researchers looked at whether geo-social network data can help. When comparing a robust data set of tweets from the Bay Area to US Census LODES data, we found that the data closely matched, and concluded that the common practice of employing LODES data to extrapolate to overall traffic demand is indeed justified. Regardless of trip purpose (e.g., shopping, regular recreational activities, dropping kids at school), the LODES data is an excellent predictor of overall road segment loads.

Moderator: Dr. Karen Philbrick, MTI's Executive Director

Presenters:
Dr. Laxmi Ramasubramanian, MTI Research Associate and Chair of San Jose State's Urban and Regional Planning Department

Dr. Jochen Albrecht, MTI Research Associate and Professor of Computational Geography at Hunter College

Jun 17, 2021 12:00 PM in Pacific Time (US and Canada)

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