Human dynamics

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Human dynamics refer to a branch of complex systems research in statistical physics such as the movement of crowds and queues and other systems of complex human interactions including statistical modelling of human networks, including interactions over communications networks.

Academic research[edit]

Human Dynamics as a branch of statistical physics: Its main goal is to understand human behavior using methods originally developed in statistical physics. Research in this area started to gain momentum in 2005 after the publication of A.-L. Barabási's seminal paper The origin of bursts and heavy tails in human dynamics.[1] that introduced a queuing model that was alleged to be capable of explaining the long tailed distribution of inter event times that naturally occur in human activity.

This paper spurred a burst of activity in this new area leading to not only further theoretical development of the Barabasi model,[2][3][4][5] its experimental verification in several different activities [5][6] and the beginning of interest in using proxy tools, such as web server logs.,[7][8][9] cell phone records[10][11] and even the rate at which registration to a major international conference occurs[12] and the distance and rate people around the globe commute from home to work.[13]

In recent years there has been a growing appetite for access to new data sources[14] that might prove useful in quantifying and understanding human behavior both at the individual and collective scales.[15]

Other usage[edit]

The term Human Dynamics or Human Dynamics as Personality Dynamics has also been used to describe a technique aimed at education and team building which has been subject to some skepticism, having been described in a Dutch newspaper as a personality course with esoteric (occult) roots.[16][17]

See also[edit]

Sense Networks


  1. ^ A.-L. Barabási (2005). "The origin of bursts and heavy tails in human dynamics.". Nature. 435 (7039): 207–211. Bibcode:2005Natur.435..207B. PMID 15889093. arXiv:cond-mat/0505371Freely accessible. doi:10.1038/nature03459. 
  2. ^ A. Vázquez (2005). "Exact results for the Barabasi model of human dynamics.". Physical Review Letters. 95 (24): 248701. Bibcode:2005PhRvL..95x8701V. PMID 16384430. arXiv:physics/0506126Freely accessible. doi:10.1103/PhysRevLett.95.248701. 
  3. ^ A. Vázquez; J. G. Oliveira; Z. Dezsö; K.-I. Goh; I. Kondor; A.-L. Barabási (2006). "Modeling bursts and heavy tails in human dynamics". Physical Review E. 73: 036127. Bibcode:2006PhRvE..73c6127V. arXiv:physics/0510117Freely accessible. doi:10.1103/PhysRevE.73.036127. 
  4. ^ Cesar A. Hidalgo (2006). "Conditions for the emergence of scaling in the inter-event time of uncorrelated and seasonal systems". Physica A. 369: 877–883. Bibcode:2006PhyA..369..877H. arXiv:cond-mat/0512278Freely accessible. doi:10.1016/j.physa.2005.12.035. 
  5. ^ a b M. Formentin; A. Lovison; A. Maritan; G. Zanzotto (2014). "Hidden scaling patterns and universality in written communication". Physical Review E. 90: 012817. PMID 25122352. doi:10.1103/PhysRevE.90.012817. 
  6. ^ J. G. Oliveira; A.-L. Barabási (2005). "Human Dynamics: The Correspondence Patterns of Darwin and Einstein.". Nature. 437 (7063): 1251. Bibcode:2005Natur.437.1251O. PMID 16251946. arXiv:physics/0511006Freely accessible. doi:10.1038/4371251a. 
  7. ^ Bruno Goncalves; Jose J. Ramasco (2008). "Human dynamics revealed through Web analytics". Physical Review E. 78: 026123. Bibcode:2008PhRvE..78b6123G. arXiv:0803.4018Freely accessible. doi:10.1103/PhysRevE.78.026123. 
  8. ^ Bruno Goncalves; Jose J. Ramasco (2009). "Towards the characterization of individual users through Web analytics". arXiv:0901.0498Freely accessible. 
  9. ^ Z. Dezsö; E. Almaas; A. Lukács; B. Rácz; I. Szakadát; A.-L. Barabási (2006). "Dynamics of information access on the web". Physical Review E. 73: 066132. Bibcode:2006PhRvE..73f6132D. doi:10.1103/PhysRevE.73.066132. 
  10. ^ J.-P. Onnela; J. Saramäki; J. Hyvönen; G. Szabó; D. Lazer; K. Kaski; J. Kertész; A.-L. Barabási (2007). "Structure and tie strengths in mobile communication networks". PNAS. 104 (18): 7332–7336. Bibcode:2007PNAS..104.7332O. PMC 1863470Freely accessible. PMID 17456605. arXiv:physics/0610104Freely accessible. doi:10.1073/pnas.0610245104. 
  11. ^ Jukka-Pekka Onnela; Jari Saramäki; Jörkki Hyvönen; Gábor Szabó; M Argollo de Menezes; Kimmo Kaski; Albert-László Barabási; János Kertèsz (2007). "Analysis of a large-scale weighted network of one-to-one human communication". New Journal of Physics Physics. 9: 179. Bibcode:2007NJPh....9..179O. arXiv:physics/0702158Freely accessible. doi:10.1088/1367-2630/9/6/179. 
  12. ^ Valentina Alfi; Giorgio Parisi; Luciano Pietronero (2007). "Conference registration: how people react to a deadline". Nature Physics. 3 (11): 746. Bibcode:2007NatPh...3..746A. doi:10.1038/nphys761. 
  13. ^ Duygu Balcan; Vittoria Colizza; Bruno Goncalves; Hao Hu; Jose J. Ramasco; Alessandro Vespignani (2009). "Title: Multiscale mobility networks and the large scale spreading of infectious diseases". arXiv:0907.3304Freely accessible. 
  14. ^ Marta C. González; Albert-László Barabási (2007). "Complex networks: From data to models". Nature Physics. 3 (4): 224–225. Bibcode:2007NatPh...3..224G. doi:10.1038/nphys581. 
  15. ^ M. Formentin; A. Lovison; A. Maritan; G. Zanzotto (2015). "New activity pattern in human interactive dynamics". Journal of Statistical Mechanics: Theory and Experiment. 9: P09006. doi:10.1088/1742-5468/2015/09/P09006. 
  16. ^ "Skepsis bekritiseert 'occulte' schooltraining". Nederlands Dagblad (in Dutch). 10 November 2009. Retrieved 4 September 2014. 
  17. ^ Nanninga, Rob (2009). "Human Dynamics. Occulte psychologie op school". Skepter (in Dutch). 22 (1). 

External links[edit]