Print

Print


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

   Barry Wellman
  _______________________________________________________________________
   FRSC                 INSNA Founder               University of Toronto
   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 $14  Kindle $9
   _______________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 31 Aug 2015 14:07:36 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=23383c3816&e=55e25a0e3e




SMART DATA: Running the Internet of Things as a Citizen Web

    Moore's law, describing the exponential explosion of processing power and data production, is currently driving a fundamental transformation of our economy and society. While processing power doubles every 18 months, data volumes double every 12 months, which means that we literally produce as much data in one year as in the entire history of humankind (i.e. all previous years). However, this is not the end of the digital revolution. More and more "things" are now equipped with communicating sensors - fridges, coffee machines, tooth brushes, smartphones and smart devices. In ten years, this will connect 150 billion "things" with each other - and with 10 billion people. This creates the "Internet of Everything" and data volumes that double every 12 hours rather than every 12 months. How will this impact our society?

http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=36bc31723b&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b06da70cc3&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=559006afc5&e=55e25a0e3e)


Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial
hierarchies, and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information. Namely, the comparison of different community detection methods, and the study of the the consistency, robustness and temporal evolution of the hierarchical modular structure of networks.

Hierarchical mutual information for the comparison of hierarchical community structures in complex networks
Juan Ignacio Perotti, Claudio Juan Tessone, Guido Caldarelli

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=0b7ed948d7&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=fecac2d427&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f10c7a1bbc&e=55e25a0e3e)



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

You can contribute to Complexity Digest selecting one of our topics (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=bb8a7655a6&e=55e25a0e3e ) and using the "Suggest" button.
==============================================
==============================================

Unsubscribe [log in to unmask] from this list:
http://unam.us4.list-manage.com/unsubscribe?u=0eb0ac9b4e8565f2967a8304b&id=f55ea67de1&e=55e25a0e3e&c=09368f37ca

_____________________________________________________________________
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.