Investigating and modeling the dynamics of long ties
Name
s42005-022-00863-w.pdf
Description
Published version
Size
909.23 KB
Format
Adobe PDF
Checksum (MD5)
647ef87cfd1421cfcb4e03aa50928282
Author(s)
Lyu, Ding
Yuan, Yuan
Wang, Lin
Wang, Xiaofan
Pentland, Alex
Date Issued
2022
Journal
Communications Physics
Publisher
Springer Science and Business Media LLC
Citation
Lyu, Ding, Yuan, Yuan, Wang, Lin, Wang, Xiaofan and Pentland, Alex. 2022. "Investigating and modeling the dynamics of long ties." Communications Physics, 5 (1).
Version
Final published version
Abstract
AbstractLong ties, the social ties that bridge different communities, are widely believed to play crucial roles in spreading novel information in social networks. However, some existing network theories and prediction models indicate that long ties might dissolve quickly or eventually become redundant, thus putting into question the long-term value of long ties. Our empirical analysis of real-world dynamic networks shows that contrary to such reasoning, long ties are more likely to persist than other social ties, and that many of them constantly function as social bridges without being embedded in local networks. Using a cost-benefit analysis model combined with machine learning, we show that long ties are highly beneficial, which instinctively motivates people to expend extra effort to maintain them. This partly explains why long ties are more persistent than what has been suggested by many existing theories and models. Overall, our study suggests the need for social interventions that can promote the formation of long ties, such as mixing people with diverse backgrounds.
MIT Department
MIT Connection Science (Research institute)
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/S42005-022-00863-W
