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SOCNET  February 2015

SOCNET February 2015

Subject:

selected [comdig] Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Tue, 3 Feb 2015 07:40:50 -0500

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (120 lines)

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




   Barry Wellman
  _______________________________________________________________________
   FRSC		              NetLab Network              INSNA Founder
   Dept of Communication & New Media    National University of Singapore
   University of Toronto                                  Toronto Canada
   http://www.chass.utoronto.ca/~wellman          twitter: @barrywellman
   NETWORKED:The New Social Operating System. Lee Rainie & Barry Wellman
   MIT Press            http://amzn.to/zXZg39      Print $15  Kindle $9
                  Old/NewCyberTimes http://bit.ly/c8N9V8
   ________________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 2 Feb 2015 21:25:37 -0600
From: Complexity Digest Administration <[log in to unmask]>
To: [log in to unmask]
Subject: [comdig] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at http://comdig.unam.mx




How Network Science Is Changing Our Understanding of Law

    The first network analysis of the entire body of European Community legislation reveals the pattern of links between laws and their resilience to change.

See it on Scoop.it (http://www.scoop.it/t/papers/p/4036228265/2015/01/29/how-network-science-is-changing-our-understanding-of-law) , via Papers (http://www.scoop.it/t/papers)



Determinants of Meme Popularity

    Online social media have greatly affected the way in which we communicate with each other. However, little is known about what are the fundamental mechanisms driving dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior and analytically show, using techniques from mathematical population genetics, that competition between memes for the limited resource of user attention leads to a type of self-organized criticality, with heavy-tailed distributions of meme popularity: a few memes "go viral" but the majority become only moderately popular. The time-dependent solutions of the model are shown to fit empirical micro-blogging data on hashtag usage, and to predict novel scaling features of the data. The presented framework, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity
structure of the social network.

Determinants of Meme Popularity
James P. Gleeson, Kevin P. O'Sullivan, Raquel A. Baņos, Yamir Moreno

http://arxiv.org/abs/1501.05956

See it on Scoop.it (http://www.scoop.it/t/papers/p/4036227571/2015/01/29/determinants-of-meme-popularity) , via Papers (http://www.scoop.it/t/papers)



Structural Patterns of the Occupy Movement on Facebook

    In this work we study a peculiar example of social organization on Facebook: the Occupy Movement -- i.e., an international protest movement against social and economic inequality organized online at a city level. We consider 179 US Facebook public pages during the time period between September 2011 and February 2013. The dataset includes 618K active users and 753K posts that received about 5.2M likes and 1.1M comments. By labeling user according to their interaction patterns on pages -- e.g., a user is considered to be polarized if she has at least the 95% of her likes on a specific page -- we find that activities are not locally coordinated by geographically close pages, but are driven by pages linked to major US cities that act as hubs within the various groups. Such a pattern is verified even by extracting the backbone structure -- i.e., filtering statistically relevant weight heterogeneities -- for both the pages-reshares and the pages-common users networks.

Structural Patterns of the Occupy Movement on Facebook
Michela Del Vicario, Qian Zhang, Alessandro Bessi, Fabiana Zollo, Antonio Scala, Guido Caldarelli, Walter Quattrociocchi

http://arxiv.org/abs/1501.07203

See it on Scoop.it (http://www.scoop.it/t/papers/p/4036214226/2015/01/29/structural-patterns-of-the-occupy-movement-on-facebook) , via Papers (http://www.scoop.it/t/papers)


Aha..... That is Interesting!: John Holland, 85 Years Young (by Jan W Vasbinder)

    John Holland is one of the few scientists, who all by themselves and by their pursuits, helped change the course of science and the wealth of human knowledge. There is hardly a field of science or problems, that is not affected by John's work on complexity and in particular, complex adaptive systems. On the occasion of his 85th birthday, many of his friends wrote about John, about facets of this remarkable man that only people close to him can know and tell.

This book collects those stories highlighting aspects of the creation of complexity science that will most likely not be found in the books on John's works.

The stories and anecdotes about his quests, his collaborators, and his friends, show his incredible mind, his boyish curiosity and explorative energy, his philosophy of life, his enormous hospitality and natural inclination to make friends.



See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4035838632/2015/01/27/aha-that-is-interesting-john-holland-85-years-young-by-jan-w-vasbinder) , via CxBooks (http://www.scoop.it/t/cxbooks)



Ricci Curvature of the Internet Topology

    Analysis of Internet topologies has shown that the Internet topology has negative curvature, measured by Gromov's "thin triangle condition", which is tightly related to core congestion and route reliability. In this work we analyze the discrete Ricci curvature of the Internet, defined by Ollivier, Lin, etc. Ricci curvature measures whether local distances diverge or converge. It is a more local measure which allows us to understand the distribution of curvatures in the network. We show by various Internet data sets that the distribution of Ricci cuvature is spread out, suggesting the network topology to be non-homogenous. We also show that the Ricci curvature has interesting connections to both local measures such as node degree and clustering coefficient, global measures such as betweenness centrality and network connectivity, as well as auxilary attributes such as geographical distances. These observations add to the richness of geometric structures in complex network
theory.

Ricci Curvature of the Internet Topology
Chien-Chun Ni, Yu-Yao Lin, Jie Gao, Xianfeng David Gu, Emil Saucan

http://arxiv.org/abs/1501.04138

See it on Scoop.it (http://www.scoop.it/t/papers/p/4035773926/2015/01/27/ricci-curvature-of-the-internet-topology) , via Papers (http://www.scoop.it/t/papers)


Introduction to the Modeling and Analysis of Complex Systems

    Introduction to the Modeling and Analysis of Complex Systems"

Hiroki Sayama

http://bingweb.binghamton.edu/~sayama/textbook/

See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4036018545/2015/01/26/introduction-to-the-modeling-and-analysis-of-complex-systems) , via CxBooks (http://www.scoop.it/t/cxbooks)



==============================================
Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

To manage subscriptions, please go to http://comdig.unam.mx/subscriptions.php

You can contribute to Complexity Digest selecting one of our topics (http://www.scoop.it/u/complexity-digest ) and using the "Suggest" button.
==============================================
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