From indirect to direct contacts on Facebook: A big‐data approach to the making of triadic network closure

Abstract

The rise of the Big Data paradigm has made it more feasible to track how personal networks evolve on social media, where auto-generated contact records and finegrained temporal data sequences help capture how and when interpersonal ties and contacts change their roles. Using a sample of matched survey data and social media records, we investigated the mechanisms by which indirect contacts ("degree-2 alters") transform into direct contacts ("degree-1 alters") from a Facebook user's (ego's) point of view. To highlight the temporal sequences, we assigned different roles to the same alters depending on how each of them is connected with ego at different periods of time. Multilevel event history analyses pinpoint several online actions and network features of ego, degree-1 alters, and degree-2 alters, as the key factors that contribute to the transformation from indirect contacts into direct contacts. RÉSUMÉL"essor du paradigme du Big Data a rendu plus réalisable le suivi de l"évolution des réseaux personnels sur les médias sociaux, où les enregistrements de contacts

A manifesto for computational sociology: The Canadian perspective

“…Anyone who has ever been involved in data collection should admire the extraordinary efforts by Lee et al. (2022) in coordinating, implementing, and integrating online and offline data collection. With the emergence of billions of social media posts every day, the conventional understanding of triadic closure in social network analysis (Granovetter, 1973) has been questioned by the enormous expansion of personal online networks in the digital era: how long does it take for an individual to connect with a friend's friend on social media?…”

“…What facilitates the transition from indirect to direct ties? By innovatively integrating a sample of representative survey data with auto‐generated Facebook contact records, Lee and colleagues (Lee et al., 2022) answer these compelling questions about social network formation by investigating how and when indirect contacts transform into direct contacts in the cyberspace. To showcase the strength of combining traditional survey and big data approaches, they use Facebook data to timestamp the formation of dyadic and triadic ties while drawing on survey data to incorporate individual sociodemographic characteristics into social network analysis.…”