According to a new study, offline social networks, revealed by co-location data, predict U.S. voting patterns more accurately than online social connections or residential sorting. Michele Tizzoni and colleagues analyzed large-scale data on co-location patterns from Meta’s Data for Good program, which collates anonymized data collected from people who enabled location services on the Facebook smartphone app. Their results are published in PNAS Nexus.
Offline interactions predict voting patterns better than online networks, finds study
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