natural experiment of social network formation and dynamics

Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social ne...

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Veröffentlicht in:Proceedings of the National Academy of Sciences - PNAS 2015-05, Vol.112 (21), p.6595-6600
Hauptverfasser: Phan, Tuan Q., Airoldi, Edoardo M.
Format: Artikel
Sprache:eng
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Zusammenfassung:Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities. Significance This paper presents an empirical analysis of the short- and long-term causal effects of a hurricane on social structure. Establishing causal relationships in social network formation and dynamics has historically been difficult because of the complexity of engineering social relations in a controlled environment, and the lack of time-resolved data about individuals' behavior. In addition, large-scale interventions of network structure are not feasible in practice. Here, we design an observational study that enables the estimation of causal effects by leveraging the locally well-defined impact of a hurricane. This aspect allows us to conceptualize the analysis of individuals’ behavior as a natural experiment, where the intervention is randomized by nature to locales, leaving only issues of balance to consider.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1404770112