Abstract

Social networks affect individuals’ economic opportunities and well-being. However, few of the factors thought to shape networks—culture, language, education, and income—were empirically validated at scale. To fill this gap, we collected a large number of social media posts from a major US metropolitan area. By associating these posts with US Census tracts through their locations, we linked socioeconomic indicators to group-level signals extracted from social media, including emotions, language, and online social ties. Our analysis shows that tracts with higher education levels have weaker social ties, but this effect is attenuated for tracts with high ratio of Hispanic residents. Negative emotions are associated with more frequent online interactions, or stronger social ties, while positive emotions are associated with weaker ties. These results hold for both Spanish and English tweets, evidencing that …

Date

January 1, 1970

Authors

Kristina Lerman, Luciano G Marin, Megha Arora, Lucas H Costa de Lima, Emilio Ferrara, David Garcia

Journal

Journal of Computational Social Science

Volume

1

Pages

209-225

Publisher

Springer Singapore