LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Starnini, M.; Baronchelli, A.; Pastor-Satorras, R. (2013)
Publisher: American Physical Society
Languages: English
Types: Article
Subjects: QC, Computer Science - Social and Information Networks, Physics - Physics and Society, Condensed Matter - Statistical Mechanics, H1
Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents which perform a random walk in a two dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1Departament de F´ısica i Enginyeria Nuclear, Universitat Polit`ecnica de Catalunya, Campus Nord B4, 08034 Barcelona, Spain 2Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston MA 02115, USA (Dated: April 19, 2013)
    • [1] M. C. Gonzalez, C. A. Hidalgo, and A.-L. Barabasi, Nature 453, 779 (2008).
    • [2] M. Jackson, Social and economic networks (Princeton University Press, 2010).
    • [3] M. E. J. Newman, Networks: An introduction (Oxford University Press, Oxford, 2010).
    • [4] J. G. Oliveira and A.-L. Barabasi, Nature 437, 1251 (2005).
    • [5] A.-L. Barabasi, Nature 435, 207 (2005).
    • [6] D. Brockmann, L. Hufnagel, and T. Geisel, Nature 439, 462 (2006).
    • [7] http://www.sociopatterns.org.
    • [8] C. Cattuto, W. Van den Broeck, A. Barrat, V. Colizza, J.-F. Pinton, and A. Vespignani, PLoS ONE 5, e11596 (2010).
    • [9] M. Starnini, A. Baronchelli, A. Barrat, and R. PastorSatorras, Phys. Rev. E 85, 056115 (2012).
    • [10] P. Holme and J. Saram¨aki, Physics Reports 519, 97 (2012).
    • [11] J. Stehle, N. Voirin, A. Barrat, C. Cattuto, V. Colizza, L. Isella, C. Regis, J.-F. Pinton, N. Khanafer, W. Van den Broeck, and P. Vanhems, BMC Medicine 9 (2011).
    • [12] M. Karsai, M. Kivel¨a, R. K. Pan, K. Kaski, J. Kert´esz, A.-L. Barab´asi, and J. Saram¨aki, Phys. Rev. E 83, 025102 (2011).
    • [13] S. Lee, L. E. C. Rocha, F. Liljeros, and P. Holme, PLoS ONE 7, e36439 (2012).
    • [14] R. Parshani, M. Dickison, R. Cohen, H. E. Stanley, and S. Havlin, Europhys. Lett. 90, 38004 (2010).
    • [15] N. Fujiwara, J. Kurths, and A. D´ıaz-Guilera, Phys. Rev. E 83, 025101 (2011).
    • [16] A. V´azquez, B. Ra´cz, A. Luka´cs, and A. L. Barab´asi, Phys. Rev. Lett. 98, 158702 (2007).
    • [17] N. Perra, B. Gonc¸alves, R. Pastor-Satorras, and A. Vespignani, Scientific Reports 2, 469 (2012).
    • [18] K. Zhao, J. Stehl´e, G. Bianconi, and A. Barrat, Phys. Rev. E 83, 056109 (2011).
    • [19] H.-H. Jo, R. K. Pan, and K. Kaski, PLoS ONE 6, e22687 (2011).
    • [20] C. Song, T. Koren, P. Wang, and A.-L. Barabasi, Nature Physics 6, 818 (2010).
    • [21] B. D. Hugues, Random walks and random environments, Vol. I, Random Walks (Clarendon Press, Oxford, 1995).
    • [22] A. Baronchelli and A. D´ıaz-Guilera, Phys. Rev. E 85, 016113 (2012).
    • [23] S. Valverde and R. V. Sol´e, Phys. Rev. E 76, 046118 (2007).
    • [24] S. Athey, E. Calvano, and S. Jha, “A theory of community formation and social hierarchy,” Working Paper (2010).
    • [25] ¿ R. M. Sapolsky, Science 308, 648 (2005).
    • [26] F. Papadopoulos, M. Kitsak, M. Serrano, M. Boguna´, and D. Krioukov, Nature 489, 537 (2012).
    • [27] L. Isella, J. Stehl´e, A. Barrat, C. Cattuto, J. Pinton, and W. Van den Broeck, J. Theor. Biol. 271, 166 (2011).
    • [28] S. Redner, A Guide To First-Passage Processes (Cambridge University Press, Cambridge, 2001).
    • [29] B. Ribeiro, N. Perra, and A. Baronchelli, arXiv preprint arXiv:1211.7052 (2012).
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article