Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
ArXiv/SSRN
We use anonymized and aggregated data from Facebook to explore the spatial structure of social networks in the New York metro area. We find that a substantial share of urban residents’ connections are to individuals who are located nearby. We also highlight the importance of transportation infrastructure in shaping urban social networks by showing that social connectedness declines faster in travel time and travel cost than it does in geographic distance. We find that areas that are more socially connected with each other have stronger commuting flows, even after controlling for geographic distance and ease of travel. We also document significant heterogeneity in the geographic breadth of social networks across New York zip codes, and show that this heterogeneity correlates with access to public transit. Zip codes with geographically broader social networks also have higher incomes, higher education levels, and more high-quality entrepreneurial activity. We also explore the social connections between New York zip codes and foreign countries, and highlight how these are related to past migration movements.
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
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