Universal spatial scales of homophily and heterophily in global amenity networks, where heterophilic mixing predicts rental value changes more effectively than amenity diversity.
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Multilevel regression and poststratification corrects socioeconomic sampling bias in CDR mobility estimates, lowering average radius of gyration by 17 percent.
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Networks of amenities reveal universal homophily and heterophily across global cities
Universal spatial scales of homophily and heterophily in global amenity networks, where heterophilic mixing predicts rental value changes more effectively than amenity diversity.
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Correcting socioeconomic bias in mobile phone mobility estimates using multilevel regression and poststratification
Multilevel regression and poststratification corrects socioeconomic sampling bias in CDR mobility estimates, lowering average radius of gyration by 17 percent.