Mario Small
Columbia University, NY·Social Science
Some neighborhoods produce many new businesses and others produce few. Who people know, and where they go, may help explain the difference.
- Fields
Social Science
Computer Science
Mathematics & Statistics
- Topics
social networks
network connectedness
entrepreneurship
- Grants
- 1 known grant, through Aug 2027
What they work on
- Build network-based measures of how well people are acquainted within and between zip codes, using data on acquaintance and contact ties, for all neighborhoods in the continental United States.
- Measure direct contact between neighborhoods from anonymous data on visits and flows of people between pairs of neighborhoods, and combine it with entrepreneurship, American Community Survey and Smart Location Database data.
- Test whether network connectedness causes higher neighborhood entrepreneurship rates across U.S. census tracts, using machine learning/AI methods and new causal analysis techniques, and release the dataset publicly.
More about the research
This project asks how the connections among people within a neighborhood, and between neighborhoods, affect how often residents start businesses. Answering this needs network measures for every community in the country, which have not existed at that scale.
Why it matters
Knowing whether neighborhood social ties drive business creation could help community planners and economic development groups support entrepreneurship where it is low. The public nationwide database will let scholars and practitioners study how neighborhood factors shape entrepreneurship and other key economic outcomes.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Constantine Kontokosta
New York University, NY·Social Science
Identify representativeness bias in smartphone mobility data, meaning which groups are over- or undercounted, and develop methods to correct it.
Elizabeth Roberto
Rice University, TX·Social Science·Early-career
Measure how road network connectivity relates to residential spatial variation and proximity to local public services across U.S. cities, using spatial and network analysis of road networks and demographic data.
Kenneth Joseph
University at Buffalo, NY·Computer Science·Early-career
Develop mixed methods combining graph-based and natural-language machine learning with qualitative analysis to identify dominant beliefs about social issues in large datasets from X and Parler.
The school
Columbia University: 89 labs on PI Pages, $1.4B a year on research, 625 research doctorates a year.
Reach out
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