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SOCNET  July 2010

SOCNET July 2010

Subject:

complexity digest gleanings

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Fri, 16 Jul 2010 23:02:38 -0400

Content-Type:

TEXT/PLAIN

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (138 lines)

*****  To join INSNA, visit http://www.insna.org  *****

lots today


  Barry Wellman
  _______________________________________________________________________

   S.D. Clark Professor of Sociology, FRSC               NetLab Director
   Department of Sociology                  725 Spadina Avenue, Room 388
   University of Toronto   Toronto Canada M5S 2J4   twitter:barrywellman
   http://www.chass.utoronto.ca/~wellman             fax:+1-416-978-3963
   Updating history:      http://chass.utoronto.ca/oldnew/cybertimes.php
  _______________________________________________________________________

  Particle Swarm Optimization , Swarm Intelligence

Abstract Excerpt: The Particle Swarm Optimizer (PSO), one of the pillars 
of Swarm Intelligence, is a remarkable algorithm for at least two reasons: 
(a) it has a very simple formulation which makes it easy to implement, 
apply, extend and hybridize, and (b) it is a constant source of complex 
and emergent phenomena, which are at the essence of swarm intelligence. 
Many people around the world are exploring PSOs and their applications.

* [14] Editorial for the special issue on Particle Swarm Optimization, 
Riccardo Poli, Andries Engelbrecht, Jim Kennedy, 2009/12, DOI: 
10.1007/s11721-009-0033-9, Swarm Intelligence Volume 3, Number 4, Pages 
243-244   [14] http://dx.doi.org/10.1007/s11721-009-0033-9

_________________________________________________________________

10. Quantifying structure in networks , Eur. Phys. J. B

Abstract: We investigate exponential families of random graph 
distributions as a framework for systematic quantification of structure in 
networks. In this paper we restrict ourselves to undirected unlabeled 
graphs. For these graphs, the counts of subgraphs with no more than k 
links are a sufficient statistics for the exponential families of graphs 
with interactions between at most k links. In this framework we 
investigate the dependencies between several observables commonly used to 
quantify structure in networks, such as the degree distribution, cluster 
and assortativity coefficients.

* [15] Quantifying structure in networks, E. Olbrich, T. Kahle, N. 
Bertschinger, N. Ay, J. Jost, 2010/07/02, DOI: 10.1140/epjb/e2010-00209-0, 
Eur. Phys. J. B
[15] http://dx.doi.org/10.1140/epjb/e2010-00209-0

--------------------------------------------------


  Information explosion on complex networks and control , Eur. Phys. J. B

Abstract: When a piece of information spreads on a complex network, error 
or distortion can occur. For a high error probability, the phenomenon of 
information explosion can occur where the number of distinct pieces of 
information on the network increases continuously with time. We construct 
a physical model to address this phenomenon. The transition to information 
explosion as the error probability increases through a critical value is 
uncovered and elucidated, and a control strategy is articulated to 
maximize the robustness of the network against information explosion, 
which is validated by both numerical computations and a mean-field based 
analysis.

* [19] Information explosion on complex networks and control, X. J. Ma, 
W.-X. Wang, Y.-C. Lai, Z. Zheng, 2010/07/02, DOI: 
10.1140/epjb/e2010-00208-1, Eur. Phys. J. B
[19] http://dx.doi.org/10.1140/epjb/e2010-00208-1

_________________________________________________________________

15. Frontiers of Collaboration: The Evolution of Social Networking ,
Knowledge@Wharton

Summary: Social networking tools such as Twitter and the emerging Google 
Wave web application are taking businesses to the frontiers of real-time 
communication and collaboration. The technology has the potential to make 
it easier to discover and share information and interact with others. But 
the key word is "potential." During a panel at the last Supernova 
technology strategy conference, experts talked about what makes the 
current crop of services more promising than those that came before, and 
the obstacles to further progress.

* [20] Frontiers of Collaboration: The Evolution of Social Networking,
2010/07/07, Knowledge@Wharton
[20] http://knowledge.wharton.upenn.edu/article.cfm?articleid=2536

_________________________________________________________________


  Invasion and expansion of cooperators in lattice populations: Prisoner's
dilemma vs. Snowdrift games , Journal of Theoretical Biology

Excerpt: Spatial structure with limited local interactions has long been 
identified as a potent promoter of cooperation in the prisoner's dilemma 
but in the spatial snowdrift game, space may actually enhance or inhibit 
cooperation. Here we investigate and link the microscopic interaction 
between individuals to the characteristics of the emerging macroscopic 
patterns generated by the spatial invasion process of cooperators in a 
world of defectors.

* [22] Invasion and expansion of cooperators in lattice populations: 
Prisoner's dilemma vs. Snowdrift games, Fu F , Nowak MA , Hauert C, July 
2010, DOI: 10.1016/j.jtbi.2010.06.042, Journal of Theoretical Biology, in 
Press * Contributed by [23] Segismundo

[22] http://dx.doi.org/10.1016/j.jtbi.2010.06.042

---------------------------------------

  Analyzing Social Media Networks with NodeXL: Insights from a Connected
World , Morgan Kaufmann

Summary:  Businesses, entrepreneurs, individuals, and government agencies 
alike are looking to social network analysis (SNA) tools for insight into 
trends, connections, and fluctuations in social media. Microsoft's NodeXL 
is a free, open-source SNA plug-in for use with Excel. It provides instant 
graphical representation of relationships of complex networked data. But 
it goes further than other SNA tools -- NodeXL was developed by a 
multidisciplinary team of experts that bring together information studies, 
computer science, sociology, human-computer interaction, and over 20 years 
of visual analytic theory and information visualization into a simple tool 
anyone can use.

* [27] Analyzing Social Media Networks with NodeXL: Insights from a 
Connected World, Derek Hansen, Ben Shneiderman, Marc A. Smith, 2010/09/01, 
Morgan Kaufmann * Contributed by [28] Anton Joha

[27]
http://www.amazon.com/dp/0123822297?tag=compldiges-20&camp=0&creative=0&linkCod
e=as1&creativeASIN=0123822297&adid=1BCTM2HB716QAH1FZRDV&
[28] mailto:[log in to unmask]

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