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SOCNET  January 2011

SOCNET January 2011

Subject:

complexity digest this week - lotsa stuff

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Sun, 16 Jan 2011 16:43:25 -0500

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (208 lines)

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


  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
  _______________________________________________________________________

  Quantitative Analysis of Culture Using Millions of Digitized Books , 
Science

Abstract: We constructed a corpus of digitized texts containing about 4% 
of all books ever printed. Analysis of this corpus enables us to 
investigate cultural trends quantitatively. We survey the vast terrain of 
culturomics, focusing on linguistic and cultural phenomena that were 
reflected in the English language between 1800 and 2000. We show how this 
approach can provide insights about fields as diverse as lexicography, the 
evolution of grammar, collective memory, the adoption of technology, the 
pursuit of fame, censorship, and historical epidemiology. Culturomics 
extends the boundaries of rigorous quantitative inquiry to a wide array of 
new phenomena spanning the social sciences and the humanities.

* [3] Quantitative Analysis of Culture Using Millions of Digitized Books, 
Jean-Baptiste Michel, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, 
Matthew K. Gray, The Google Books Team, Joseph P. Pickett, Dale Hoiberg, 
Dan Clancy, Peter Norvig, Jon Orwant, Steven Pinker, Martin A. Nowak, and 
Erez Lieberman Aiden, 2011/01/14, DOI: 10.1126/science.1199644, Science 
Vol. 331 no. 6014 pp. 176-182

[3] http://dx.doi.org/10.1126/science.1199644
-------------------

Communication: Mapping science , Nature

Excerpt:    [11]

In the Atlas of Science, information scientist Katy Börner highlights 
examples that summarize the evolution of research and its interlocking 
communities in pictorial form. The book accompanies Börner's ambitious 
travelling exhibitions, Places & Spaces: Mapping Science, an ongoing 
programme of well-crafted visual presentations that have conveyed aspects 
of science to the public in libraries and museums since 2005 ( [12] 
http://scimaps.org).

* [13] Communication: Mapping science, Ben Shneiderman, 2010/12/22, DOI:
10.1038/4681037a, Nature 468, 1037

[11]
http://www.amazon.com/gp/product/0262014459?ie=UTF8&tag=complexes-20&linkCode=as2&c
amp=1789&creative=9325&creativeASIN=0262014459
[12] http://scimaps.org
[13] http://dx.doi.org/10.1038/4681037a

_________________________________________________________________

  Continuous-time model of structural balance , PNAS

Excerpt: It is not uncommon for certain social networks to divide into two 
opposing camps in response to stress. This happens, for example, in 
networks of political parties during winner-takes-all elections, in 
networks of companies competing to establish technical standards, and in 
networks of nations faced with mounting threats of war. A simple model for 
these two-sided separations is the dynamical system dX/dt = X^2, where X 
is a matrix of the friendliness or unfriendliness between pairs of nodes 
in the network. (...)

* [14] Continuous-time model of structural balance, Seth A. Marvel,  Jon
Kleinberg,  Robert D. Kleinberg,  Steven H. Strogatz, 2011/01/03, DOI:
10.1073/pnas.1013213108, PNAS, Published online before print

[14] http://dx.doi.org/10.1073/pnas.1013213108

_________________________________________________________________

08. Modular Random Boolean Networks , arXiv

Abstract: Random Boolean networks (RBNs) have been a popular model of 
genetic regulatory networks for more than four decades. However, most RBN 
studies have been made with regular topologies, while real regulatory 
networks have been found to be modular. In this work, we extend classical 
RBNs to define modular RBNs. Statistical experiments and analytical 
results show that modularity has a strong effect on the properties of 
RBNs. In particular, modular RBNs are closer to criticality than regular 
RBNs.

* [15] Modular Random Boolean Networks, Rodrigo Poblanno-Balp and Carlos
Gershenson, 2011/01/10, arXiv:1101.1893

[15] http://arXiv.org/abs/1101.1893

_________________________________________________________________

  An Agent-Based Approach to Self-Organized Production , arXiv

Excerpt: The chapter describes the modeling of a material handling system 
with the production of individual units in a scheduled order. The units 
represent the agents in the model and are transported in the system which 
is abstracted as a directed graph. Since the hindrances of units on their 
path to the destination can lead to inefficiencies in the production, the 
blockages of units are to be reduced. Therefore, the units operate in the 
system by means of local interactions in the conveying elements and 
indirect interactions based on a measure of possible hindrances. If most 
of the units behave cooperatively ("socially"), the blockings in the 
system are reduced.

* [16] An Agent-Based Approach to Self-Organized Production, Thomas 
Seidel, Jeanette Hartwig, Richard L. Sanders, and Dirk Helbing, 
2010/12/21, arXiv:1012.4645
[16] http://arXiv.org/abs/1012.4645

_________________________________________________________________

  The AHA! Experience: Creativity Through Emergent Binding in Neural 
Networks
, Cognitive Science

Abstract: Many kinds of creativity result from combination of mental 
representations. This paper provides a computational account of how 
creative thinking can arise from combining neural patterns into ones that 
are potentially novel and useful. We defend the hypothesis that such 
combinations arise from mechanisms that bind together neural activity by a 
process of convolution, a mathematical operation that interweaves 
structures. We describe computer simulations that show the feasibility of 
using convolution to produce emergent patterns of neural activity that can 
support cognitive and emotional processes underlying human creativity.

* [17] The AHA! Experience: Creativity Through Emergent Binding in Neural
Networks, Paul Thagard, Terrence C. Stewart, 2011/01-02, DOI:
10.1111/j.1551-6709.2010.01142.x, Cognitive Science Volume 35, Issue 1, 
pages
133, January/February 2011

[17] http://dx.doi.org/10.1111/j.1551-6709.2010.01142.x

_________________________________________________________________

  Selection in Scientific Networks , arXiv

Excerpt: One of the most interesting scientific challenges nowadays deals 
with the analysis and the understanding of complex networks' dynamics. A 
major issue is the definition of new frameworks for the exploration of the 
dynamics at play in real dynamic networks. Here, we focus on scientific 
communities by analyzing the "social part" of Science through a 
descriptive approach that aims at identifying the social determinants 
(e.g. goals and potential interactions among individuals) behind the 
emergence and the resilience of scientific communities.

* [21] Selection in Scientific Networks, Walter Quattrociocchi, Frederic
Amblard, 2010/12/20, arXiv:1012.4396

[21] http://arXiv.org/abs/1012.4396

_________________________________________________________________

  Percolate or die: Multi-percolation decides the struggle between
competing innovations , arXiv

Abstract: Competition is one of the most fundamental phenomena in physics, 
biology and economics. Recent studies of the competition between 
innovations have highlighted the influence of switching costs and 
interaction networks, but the problem is still puzzling. We introduce a 
model that reveals a novel multi-percolation process, which governs the 
struggle of innovations trying to penetrate a market. We find that 
innovations thrive as long as they percolate in a population, and one 
becomes dominant when it is the only one that percolates. Besides offering 
a theoretical framework to understand the diffusion of competing 
innovations in social networks, our results are also relevant to model 
other problems such as opinion formation, political polarization, survival 
of languages and the spread of health behavior.

* [22] Percolate or die: Multi-percolation decides the struggle between 
competing innovations, Carlos P. Roca, Moez Draief and Dirk Helbing, 
2011/01/04, arXiv:1101.0775

[22] http://arXiv.org/abs/1101.0775

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

  Self-Organizing Systems , Springer

About: This book constitutes the refereed proceedings of the 5th 
International Workshop on Self-Organizing Systems, IWSOS 2011, held in 
Karlsruhe, Germany, in February 2011. The 9 revised full papers presented 
together with 1 invited paper were carefully selected from 25 initial 
submissions. It was the 5th workshop in a series of multidisciplinary 
events dedicated to self-organization in networked systems with main focus 
on communication and computer networks. The papers address theoretical 
aspects of self-organization as well as applications in communication and 
computer networks and robot networks.

* [27] Self-Organizing Systems, Bettstetter, Christian; Gershenson, Carlos
(Eds.), 2011/03/08, DOI: 978-3-642-19166-4, Springer
http://www.springer.com/computer/communication+networks/book/978-3-642-19166-4 
_________________________________________________________________


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