Print

Print


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


Reminder, I select rapidly from full Complexity Digest every week.
I do not rewrite.
http://comdig.unam.mx
for fuller versions

  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
  _______________________________________________________________________

  Nicholas Christakis: How social networks predict epidemics , TED.com

About this talk: After mapping humans' intricate social networks, Nicholas 
Christakis and colleague James Fowler began investigating how this 
information could better our lives. Now, he reveals his hot-off-the-press 
findings: These networks can be used to detect epidemics earlier than 
ever, from the spread of innovative ideas to risky behaviors to viruses 
(like H1N1).

* [10] Nicholas Christakis: How social networks predict epidemics, 
2010/09,
TED.com
* VIDEO - [11] Watch this talk

http://www.ted.com/talks/nicholas_christakis_how_social_networks_predict_epidemics.html
[11]
http://www.ted.com/talks/nicholas_christakis_how_social_networks_predict_epidemics.html

_________________________________________________________________

05.01. Steven Johnson: Where good ideas come from , TED.com

About this talk: People often credit their ideas to individual "Eureka!" 
moments. But Steven Johnson shows how history tells a different story. His 
fascinating tour takes us from the "liquid networks" of London's coffee 
houses to Charles Darwin's long, slow hunch to today's high-velocity web.

* [12] Steven Johnson: Where good ideas come from, 2010/09, TED.com
* VIDEO - [13] Watch this talk

[12] 
http://www.ted.com/talks/steven_johnson_where_good_ideas_come_from.html
http://www.ted.com/talks/steven_johnson_where_good_ideas_come_from.html

_________________________________________________________________

  Peer-Review in a World with Rational Scientists: Toward Selection of the
Average , SFI Working Papers

Excerpt: One of the virtues of peer review is that it provides a 
self-regulating selection mechanism for scientific work, papers and 
projects. Peer review as a selection mechanism is hard to evaluate in 
terms of its efficiency. Serious efforts to understand its strengths and 
weaknesses have not yet lead to clear answers. In theory peer review works 
if the involved parties (editors and referees) conform to a set of 
requirements, such as love for high quality science, objectiveness, and 
absence of biases, nepotism, friend and clique networks, selfishness, etc. 
If these requirements are violated, what is the effect on the selection of 
high quality work? We study this question with a simple agent based model. 
In particular we are interested in the effects of rational referees, who 
might not have any incentive to see high quality work other than their own 
published or promoted. We find that a small fraction of incorrect (selfish 
or rational) referees can drastically reduce the quality of the published 
(accepted) scientific standard.

* [18] Peer-Review in a World with Rational Scientists: Toward Selection 
of the Average, Stefan Thurner, Rudolf Hanel, DOI: SFI-WP 10-09-016, SFI 
Working Papers

[18]
http://www.santafe.edu/research/working-papers/abstract/dc59aa3f002f8f6e9c4ee88b858dda5a/

_________________________________________________________________

  Line graphs of weighted networks for overlapping communities , Eur. Phys. 
J. B

Abstract: In this paper, we develop the idea to partition the edges of a 
weighted graph in order to uncover overlapping communities of its nodes. 
Our approach is based on the construction of different types of weighted 
line graphs, i.e. graphs whose nodes are the links of the original graph, 
that encapsulate differently the relations between the edges. Weighted 
line graphs are argued to provide an alternative, valuable representation 
of the system's topology, and are shown to have important applications in 
community detection, as the usual node partition of a line graph naturally 
leads to an edge partition of the original graph. This identification 
allows us to use traditional partitioning methods in order to address the 
long-standing problem of the detection of overlapping communities. We 
apply it to the analysis of different social and geographical networks.

* [20] Line graphs of weighted networks for overlapping communities, T. S. 
Evans and R. Lambiotte, 2010/09/13, DOI: 10.1140/epjb/e2010-00261-8, Eur. 
Phys. J. B

[20] http://dx.doi.org/10.1140/epjb/e2010-00261-8

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

  Adaptive network models of swarm dynamics , arXiv

Abstract: A simple adaptive network model describing recent swarming 
experiments is introduced. By exploiting an analogy with human 
decision-making models, its dynamics is captured using a low-dimensional 
system of equations permitting analytical investigation. The model 
reproduces several characteristic features of swarms, including: 
spontaneous symmetry breaking, noise- and density-driven order-disorder 
transitions that can be of first or second order, intermittency, and 
metastable configurations displaying memory effects. By considering only 
minimal components of the swarming dynamics, it highlights the essential 
elements required to reproduce the observed behavior.

* [25] Adaptive network models of swarm dynamics, Cristián Huepe, Gerd
Zschaler, Anne-Ly Do, Thilo Gross, 2010/09/13, arXiv:1009.2349
[25] http://arXiv.org/abs/1009.2349

_________________________________________________________________

. Econophysics and Companies: Statistical Life and Death in Complex
Business Networks , Cambridge University Press

Summary:  Econophysics is an emerging interdisciplinary field that takes 
advantage of the concepts and methods of statistical physics to analyse 
economic phenomena. This book expands the explanatory scope of 
econophysics to the real economy by using methods from statistical physics 
to analyse the success and failure of companies. Using large data sets of 
companies and income-earners in Japan and Europe, the authors show how 
these methods allow us to analyse companies, from huge corporations to 
small firms. They then show how successful this approach is in explaining 
a wide range of recent findings relating to the dynamics of companies.

* [36] Econophysics and Companies: Statistical Life and Death in Complex
Business Networks, Hideaki Aoyama et al., 2010/09/15, Cambridge University 
Press

http://www.amazon.com/dp/0521191491?tag=compldiges-20&camp=0&creative=0&linkCode=as1&creativeASIN=0521191491&adid=19V012D6KVD8T1SZSZWC&


_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.