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Correlated Dynamics in Egocentric Communication Networks

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  • Márton Karsai
  • Kimmo Kaski
  • János Kertész

Abstract

We investigate the communication sequences of millions of people through two different channels and analyse the fine grained temporal structure of correlated event trains induced by single individuals. By focusing on correlations between the heterogeneous dynamics and the topology of egocentric networks we find 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. We compare the directional balance of calls and short messages within bursty trains to the average on the actual link and show that for the trains of voice calls the imbalance is significantly enhanced, while for short messages the balance within the trains increases. These effects can be partly traced back to the technological constraints (for short messages) and partly to the human behavioural features (voice calls). We define a model that is able to reproduce the empirical results and may help us to understand better the mechanisms driving technology mediated human communication dynamics.

Suggested Citation

  • Márton Karsai & Kimmo Kaski & János Kertész, 2012. "Correlated Dynamics in Egocentric Communication Networks," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
  • Handle: RePEc:plo:pone00:0040612
    DOI: 10.1371/journal.pone.0040612
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    References listed on IDEAS

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    1. C. Anteneodo & R. D. Malmgren & D. R. Chialvo, 2010. "Poissonian bursts in e-mail correspondence," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 389-394, June.
    2. Ciro Cattuto & Wouter Van den Broeck & Alain Barrat & Vittoria Colizza & Jean-François Pinton & Alessandro Vespignani, 2010. "Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks," PLOS ONE, Public Library of Science, vol. 5(7), pages 1-9, July.
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    Cited by:

    1. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Rabbani, Fereshteh & Khraisha, Tamer & Abbasi, Fatemeh & Jafari, Gholam Reza, 2021. "Memory effects on link formation in temporal networks: A fractional calculus approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    3. Jun Gui & Zeyu Zheng & Dianzheng Fu & Zihao Yang & Yuan Gao & Zhi Liu, 2020. "Dynamics of calling activity to toll-free numbers in China," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-16, March.
    4. Wang, Wenjun & Yuan, Ning & Pan, Lin & Jiao, Pengfei & Dai, Weidi & Xue, Guixiang & Liu, Dong, 2015. "Temporal patterns of emergency calls of a metropolitan city in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 846-855.

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