Using location-based social network data for activity intensity analysis: A case study of New York City

Abstract

Location-based social networks (LBSN) are social media sites where users check-in at venues and share content linked to their geo-locations. LBSN, considered to be a novel data source, contain valuable information for urban planners and researchers. While earlier research efforts focused either on disaggregate patterns or aggregate analysis of social and temporal attributes, no attempt has been made to relate the data to transportation planning outcomes. To that extent, the current study employs LBSN service-based data for an aggregate-level transportation planning exercise by developing land-use planning models. Specifically, we employ check-in data aggregated at the census tract level to develop a quantitative model for activity intensity as a function of land use and built-environment attributes for the New York City (NYC) region. A statistical exercise based on clustering of census tracts and negative binomial regression analyses are adopted to analyze the aggregated data. We demonstrate the implications of the estimated models by presenting the spatial aggregation profiling based on the model estimates. The findings provide insights on relative differences of activity engagements across the urban region. The proposed approach thus provides a complementary analysis tool to traditional transportation planning exercises.

Author Biographies

Haluk Laman, University of Central Florida
Research Assistant Department of Civil, Environmental & Construction Engineering
Shamsunnahar Yasmin, University of Central Florida
Postdoctoral Associate Department of Civil, Environmental & Construction Engineering
Naveen Eluru, University of Central Florida
Associate Professor Department of Civil, Environmental and Construction Engineering

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Published
2019-10-09
How to Cite
Laman, H., Yasmin, S., & Eluru, N. (2019). Using location-based social network data for activity intensity analysis: A case study of New York City. Journal of Transport and Land Use, 12(1). https://doi.org/10.5198/jtlu.2019.1470
Section
Articles