Temporal network

A temporal network, also known as a time-varying network, is a network whose links are active only at certain points in time. Each link carries information on when it is active, along with other possible characteristics such as a weight. Time-varying networks are of particular relevance to spreading processes, like the spread of information and disease, since each link is a contact opportunity and the time ordering of contacts is included.

Examples of time-varying networks include communication networks where each link is relatively short or instantaneous, such as phone calls or e-mails.[1][2] Information spreads over both networks, and some computer viruses spread over the second. Networks of physical proximity, encoding who encounters whom and when, can be represented as time-varying networks.[3] Some diseases, such as airborne pathogens, spread through physical proximity. Real-world data on time resolved physical proximity networks has been used to improve epidemic modeling.[4] Neural networks and brain networks can be represented as time-varying networks since the activation of neurons are time-correlated.[5]

Time-varying networks are characterized by intermittent activation at the scale of individual links. This is in contrast to various models of network evolution, which may include an overall time dependence at the scale of the network as a whole.

  1. ^ Karsai, M.; Perra, N.; Vespignani, A. (2015). "Time-varying networks and the weakness of strong ties" (PDF). Sci. Rep. 4: 4001. arXiv:1303.5966. Bibcode:2014NatSR...4E4001K. doi:10.1038/srep04001. PMC 3918922. PMID 24510159.
  2. ^ J.-P. Eckmann, E. Moses, and D. Sergi. Entropy of dialogues creates coherent structures in e-mail traffic" Proc. Natl. Acad. Sci. USA 2004; 101:14333–14337. https://www.weizmann.ac.il/complex/EMoses/pdf/EntropyDialogues.pdf
  3. ^ Eagle, N.; Pentland, A. (2006). "Reality mining: sensing complex social systems". Pers Ubiquit Comput. 10 (4): 255–268. doi:10.1007/s00779-005-0046-3. S2CID 1766202.
  4. ^ Stehle, J.; Voirin, N.; Barrat, A.; Cattuto, C.; Colizza, V.; Isella, L.; Regis, C.; Pinton, J.-F.; Khanafer, N.; Vanhems, P. (2011). "Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees". BMC Medicine. 9: 87. arXiv:1108.4841. doi:10.1186/1741-7015-9-87. PMC 3162551. PMID 21771290.
  5. ^ Holme, P.; Saramäki, J. (2012). "Temporal Networks". Phys. Rep. 519 (3): 102. arXiv:1108.1780. Bibcode:2012PhR...519...97H. doi:10.1016/j.physrep.2012.03.001. S2CID 1920175.

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