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Small Business Economics
Published in: Small Business Economics 3/2020

28-06-2019

Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA

Authors: Martin Obschonka, Neil Lee, Andrés Rodríguez-Pose, Johannes C. Eichstaedt, Tobias Ebert

Published in: Small Business Economics | Issue 3/2020

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Abstract

There is increasing interest in the potential of artificial intelligence and Big Data (e.g., generated via social media) to help understand economic outcomes. But can artificial intelligence models based on publicly available Big Data identify geographical differences in entrepreneurial personality or culture? We use a machine learning model based on 1.5 billion tweets by 5.25 million users to estimate the Big Five personality traits and an entrepreneurial personality profile for 1772 US counties. The Twitter-based personality estimates show substantial relationships to county-level entrepreneurship activity, accounting for 20% (entrepreneurial personality profile) and 32% (Big Five traits) of the variance in local entrepreneurship, even when controlling for other factors that affect entrepreneurship. Whereas more research is clearly needed, our findings have initial implications for research and practice concerned with entrepreneurial regions and eco-systems, and regional economic outcomes interacting with local culture. The results suggest, for example, that social media datasets and artificial intelligence methods have the potential to deliver comparable information on the personality and culture of regions than studies based on millions of questionnaire-based personality tests.
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Appendix
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Footnotes
1
The threshold of 100 km is informed by previous research showing that commuting (as a proxy for an individual’s daily available interaction radius) becomes cumbersome if it exceeds 80–100 km (e.g., Helminen and Ristimäki 2007). We also tested alternative distance thresholds, leading to very similar distributional patterns.
 
2
The University of Pennsylvania IRB approved this study (protocol no. 813866).
 
3
We note that while we collect Twitter data over a period of time, we do so to maximize the sample rather than collect a panel indicator.
 
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Metadata
Title
Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA
Authors
Martin Obschonka
Neil Lee
Andrés Rodríguez-Pose
Johannes C. Eichstaedt
Tobias Ebert
Publication date
28-06-2019
Publisher
Springer US
Published in
Small Business Economics / Issue 3/2020
Print ISSN: 0921-898X
Electronic ISSN: 1573-0913
DOI
https://doi.org/10.1007/s11187-019-00204-2

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