Lifestyle Enclaves in the Instagram City?

Commentators and scholars view both social media and cities as sites of fragmentation. Since both urban dwellers and social media users tend to form assortative social ties, so the reasoning goes, identity-based divisions are fortified and polarization is exacerbated in digital and urban spaces. Dra...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Social media + society 2020-07, Vol.6 (3)
Hauptverfasser: Boy, John D., Uitermark, Justus
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Commentators and scholars view both social media and cities as sites of fragmentation. Since both urban dwellers and social media users tend to form assortative social ties, so the reasoning goes, identity-based divisions are fortified and polarization is exacerbated in digital and urban spaces. Drawing on a dataset of 34.4 million interactions among Amsterdam Instagram users over half a year, this article seeks to gauge the level of fragmentation that occurs at the interface of digital and urban spaces. We find some evidence for fragmentation: users form clusters based on shared tastes and leisure activities, and these clusters are embedded in four distinct lifestyle zones at the interface of social media and the city. However, we also find connections that span divisions. Similarly, places that are tagged by Instagram users generally include a heterogeneity of clusters. While there is evidence that Instagram users sort into groups, there is no evidence that these groups are isolated from one another. In fact, our findings suggest that Instagram enables ties across different groups and mitigates against particularity and idiosyncrasy. These findings have important implications for how we should understand and study social media in the context of everyday life. Scholars should not only look for evidence of division through standard network analytic techniques like community detection, but also allow for countervailing tendencies.
ISSN:2056-3051
2056-3051
DOI:10.1177/2056305120940698