Triadic embeddedness structure in family networks predicts mobile communication response to a sudden natural disaster

Jayson S. JIA*, Yiwei LI, Xin LU, Yijian NING, Nicholas A. CHRISTAKIS, Jianmin JIA*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

Kinship networks are a fundamental social unit in human societies, and like social networks in general, provide social support in times of need. Here, we investigate the impact of sudden environmental shock, the Ms 7.0 2013 Ya’an earthquake, on the mobile communications patterns of local families, which we operationalize using anonymized individual-level mobile telecommunications metadata from family plan subscribers of a major carrier (N = 35,565 people). We demonstrate that families’ communications dynamics after the earthquake depended on their triadic embeddedness structure, a structural metric we propose that reflects the number of dyads in a family triad that share social ties. We find that individuals in more embedded family structures were more likely to first call other family plan members and slower in calling non-family ties immediately after the earthquake; these tendencies were stronger at higher earthquake intensity. In the weeks after the event, individuals in more embedded family structures had more reciprocal communications and contacted more social ties in their broader social network. Overall, families that are structurally more embedded displayed higher levels of intra-family coordination and mobilization of non-family social connections.
Original languageEnglish
Article number4286
Number of pages12
JournalNature Communications
Volume12
Issue number1
Early online date13 Jul 2021
DOIs
Publication statusE-pub ahead of print - 13 Jul 2021

Bibliographical note

Funding Information:
We thank Mark Granovetter, Robert Weyer Jr., and David Rand for their feedback. We thank an unnamed national carrier in China for providing the anonymized data, and their staff for their assistance in data preparation. J.S.J. is supported by the Research Grants Council of Hong Kong (C7105-20G, 14505217, and 17506316). J.J. is supported by the National Natural Science Foundation of China (72042009 and 72074072). Y.L. is supported by the Lam Woo Research Fund at Lingnan University. X.L. is supported by the National Natural Science Foundation of China (91846301, 82041020, 72025405, and 72088101).

Publisher Copyright:
© 2021, The Author(s).

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