2007/12/31 by César A. Hidalgo, Cesar A. Hidalgo, Carlos Rodríguez‐Sickert +1 · 201 citations
Engineering · Mathematics · Physics and Astronomy · Psychology · Social Sciences · #Artificial intelligence #Cluster analysis #Complex Network Analysis Techniques #Computer science #Engineering #Human Mobility and Location-Based Analysis #Mathematics #Mobile phone #Network dynamics #Opinion Dynamics and Social Influence #Persistence (discontinuity) #Phone #Psychology #Reciprocal #Reciprocity (cultural anthropology) #Redundancy (engineering) #Social psychology #Telecommunications #physics.soc-ph
paper · pdf · doi:10.1016/j.physa.2008.01.073
published in Physica A Statistical Mechanics and its Applications 387(12), 3017-3024 (Elsevier BV)
openalex publication_date 2008/01/20 · arxiv created 2008/02/11 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The empirical study of network dynamics has been limited by the lack of longitudinal data. Here we introduce a quantitative indicator of link persistence to explore the correlations between the structure of a mobile phone network and the persistence of its links. We show that persistent links tend to be reciprocal and are more common for people with low degree and high clustering. We study the redundancy of the associations between persistence, degree, clustering and reciprocity and show that reciprocity is the strongest predictor of tie persistence. The method presented can be easily adapted to characterize the dynamics of other networks and can be used to identify the links that are most likely to survive in the future.