Calling patterns in human communication dynamics

@article{Jiang2013CallingPI,
  title={Calling patterns in human communication dynamics},
  author={Zhi-Qiang Jiang and Wen-Jie Xie and Ming-Xia Li and Boris Podobnik and Wei‐Xing Zhou and Harry Eugene Stanley},
  journal={Proceedings of the National Academy of Sciences},
  year={2013},
  volume={110},
  pages={1600 - 1605}
}
Modern technologies not only provide a variety of communication modes (e.g., texting, cell phone conversation, and online instant messaging), but also detailed electronic traces of these communications between individuals. These electronic traces indicate that the interactions occur in temporal bursts. Here, we study intercall duration of communications of the 100,000 most active cell phone users of a Chinese mobile phone operator. We confirm that the intercall durations follow a power-law… 

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References

SHOWING 1-10 OF 36 REFERENCES
Uncovering individual and collective human dynamics from mobile phone records
TLDR
The mean collective behavior at large scales is studied and it is shown that the interevent time of consecutive calls is heavy-tailed, which has implications for dynamics of spreading phenomena in social networks.
Structure and tie strengths in mobile communication networks
TLDR
It is found that, when it comes to information diffusion, weak and strong ties are both simultaneously ineffective, and this coupling significantly slows the diffusion process, resulting in dynamic trapping of information in communities.
The origin of bursts and heavy tails in human dynamics
TLDR
It is shown that the bursty nature of human behaviour is a consequence of a decision-based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times.
Empirical Analysis on the Human Dynamics of a Large-Scale Short Message Communication System
TLDR
A real-life huge dataset of short message communication with 6326713 users and 37577781 records during the 2006 Chinese New Year is analyzed and shows that the number of shortmessage sendings, the interevent time between two consecutive short message sendings and the response time all follow heavy-tailed distribution.
Correlated Dynamics in Egocentric Communication Networks
TLDR
It is found that the bursty trains usually evolve for pairs of individuals rather than for the ego and his/her several neighbours, thus burstiness is a property of the links rather than of the nodes.
Analysis of a large-scale weighted network of one-to-one human communication
TLDR
A positive correlation between the overlap and weight of a link is reported, thus providing strong quantitative evidence for the weak ties hypothesis, a central concept in social network analysis.
A Poissonian explanation for heavy tails in e-mail communication
TLDR
It is demonstrated that the approximate power-law scaling of the inter-event time distribution is a consequence of circadian and weekly cycles of human activity, and a cascading nonhomogeneous Poisson process is proposed that explicitly integrates these periodic patterns in activity with an individual's tendency to continue participating in an activity.
Understanding individual human mobility patterns
TLDR
The trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period is studied, finding that, in contrast with the random trajectories predicted by the prevailing Lévy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity.
Emergence of Bursts and Communities in Evolving Weighted Networks
TLDR
This paper studies how the community structure and the bursty dynamics emerge together in a simple evolving weighted network model and shows that the interplay of these mechanisms leads to the emergence of heavy tailed inter-event time distribution and the evolution of Granovetter-type community structure.
...
...