The Dynamics of a Mobile Phone Network
arXiv:0712.4031 · doi:10.1016/j.physa.2008.01.073
Abstract
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.
References in corpus (13)
- Emergence of scaling in random networks
- Assortative mixing in networks
- Mixing patterns in networks
- Evolution of the social network of scientific collaborations
- Structure and tie strengths in mobile communication networks
- Quantifying social group evolution
- Scale-free topology of e-mail networks
- The statistical mechanics of networks
- Measuring preferential attachment for evolving networks
- The topological relationship between the large-scale attributes and local interaction patterns of complex networks
- Structure and Time-Evolution of an Internet Dating Community
- The effect of social interactions in the primary life cycle of motion pictures
- Stationary States of a Random Copying Mechanism over a Complex Networks
Cited by in corpus (37)
- Understanding individual human mobility patterns
- Structure and dynamics of molecular networks: A novel paradigm of drug discovery. A comprehensive review
- Understanding the spreading patterns of mobile phone viruses
- Measuring large-scale social networks with high resolution
- The dynamical strength of social ties in information spreading
- A city of cities: Measuring how 15-minutes urban accessibility shapes human mobility in Barcelona
- Happiness and the Patterns of Life: A Study of Geolocated Tweets
- An analytical framework to nowcast well-being using mobile phone data
- Data-driven generation of spatio-temporal routines in human mobility
- Sex differences in intimate relationships
- From seconds to months: multi-scale dynamics of mobile telephone calls
- Birth and death of links control disease spreading in empirical contact networks
- Quantifying Information Flow During Emergencies
- Drug-therapy networks and the predictions of novel drug targets
- Levy stable two-sided distributions: exact and explicit densities for asymmetric case
- Sampling from Social Networks with Attributes
- Efficient allocation of heterogeneous response times in information spreading process
- Structural differences between open and direct communication in an online community
- Impact of temporal network structures on the speed of consensus formation in opinion dynamics
- Are Safer Looking Neighborhoods More Lively? A Multimodal Investigation into Urban Life
- Reciprocity of mobile phone calls
- Time allocation in social networks: correlation between social structure and human communication dynamics
- Communication activity in social networks: growth and correlations
- Neurosciences and 6G: Lessons from and Needs of Communicative Brains
- Influence of Personal Preferences on Link Dynamics in Social Networks
- A survey of results on mobile phone datasets analysis
- Complex Systems Science meets 5G and IoT
- Exploiting all phone media? A multidimensional network analysis of phone users' sociality
- The Dynamics of Initiative in Communication Networks
- Connectivity and Community Structure of Online and Register-based Social Networks
- How Do Hyperedges Overlap in Real-World Hypergraphs? -- Patterns, Measures, and Generators
- Limits of Friendship Networks in Predicting Epidemic Risk
- GeoDBLP: Geo-Tagging DBLP for Mining the Sociology of Computer Science
- Constructing a taxonomy of fine-grained human movement and activity motifs through social media
- Algorithms for Generating Large-scale Clustered Random Graphs
- Growing Networks with Super-Joiners
- Temporal patterns behind the strength of persistent ties