Find Your Circles presentation

Network is
always the answer

Alberto Asuero Arroyo Carlos Herrera Yagüe
Soft Engineer @Geographica PhD Candidate @UPM
@alasarr @cyague

Thursday, December 8, 2011

@ﬁndyourcircles


This structure is optimal in many
ways (humidity, temperature...).

@ﬁndyourcircles


This structure is optimal in many
ways (humidity, temperature...).

How was it made by such a
simple animal?

@ﬁndyourcircles


Probably is more likely to explain it
by considering it was made by
many of these. A map of the
interactions may be the key.

@ﬁndyourcircles


How to sort results in a web search?

java.com

en.wikipedia.org/Java

forodejava.com

aprender-java.blogspot.com

@ﬁndyourcircles



Semantics?
java.com


forodejava.com


@ﬁndyourcircles



Semantics?
java.com
Number of visits?

forodejava.com


@ﬁndyourcircles



Semantics?
java.com
Number of visits?

forodejava.com What if we draw
the web as a network?


@ﬁndyourcircles


java.com

forodejava.com aprender-java.blog


@ﬁndyourcircles


How to group friends in a facebook proﬁle?

@ﬁndyourcircles



Name Age Lives in Is from College
Victor 25 Usal
Javier 25 Madrid Salamanca Upco
Miguel 25
Pepe 25 Madrid Salamanca Uax
Ana 24 Madrid Santander Upm
Inés 25 Santander Salamanca
Alberto 25 Sevilla Huelva Uam

@ﬁndyourcircles


Smart lists solution

Name Age Lives in Is from College
Victor 25 Usal
Javier 25 Madrid Salamanca Upco
Miguel 25 Salamanca
Pepe 25 Madrid Salamanca Uax
Ana 24 Madrid Santander Upm
Inés 25 Santander Salamanca
Alberto 25 Sevilla Huelva Uam
Carlos 25 Madrid Salamanca Upm

@ﬁndyourcircles


And only you came up with this?


★Yong-Yeol Ahn, James P. Bagrow and Sune Lehmann, "Link communities reveal multiscale complexity in networks", Nature 455 (2010): 761--764,arxiv:0903.3178 [Lehmann's
blog-post on this]
★Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing, "Mixed membership stochastic blockmodels", arxiv:0705.4485
★Nelson Augusto Alves, "Unveiling community structures in weighted networks", physics/0703087
★Leonardo Angelini, Stefano Boccaletti, Daniele Marinazzo, Mario Pellicoro, and Sebastiano Stramaglia, "Fast identification of network modules by optimization of ratio
association", cond-mat/0610182
★L. Angelini, D. Marinazzo, M. Pellicoro and S. Stramaglia, "Natural clustering: the modularity approach", cond-mat/0607643
★Alex Arenas, Javier Borge-Holthoefer, Sergio Gomez, Gorka Zamora-Lopez, "Optimal map of the modular structure of complex networks", New Journal of Physics 12 (2010):
053009, arxiv:0911.2651
★A. Arenas, J. Duch, A. Fernandez, S. Gomez, "Size reduction of complex networks preserving modularity", physics/0702015 [Do you really need all those links? Wouldn't your
life be simpler if you could just ignore some of them?]
★Alex Arenas, Alberto Fernandez, Sergio Gomez, "Multiple resolution of the modular structure of complex networks", physics/0703218
★Alex Arenas, Alberto Fernandez, Santo Fortunato, Sergio Gomez, "Motif-based communities in complex networks", arxiv:0710.0059
★Jim Bagrow and Erik Bollt, "A Local Method for Detecting Communities",cond-mat/0412482
★James Bagrow, Erik Bollt, Luciano da F. Costa, "Network Structure Revealed by Short Cycles", cond-mat/0612502
★Brian Ball, Brian Karrer, M. E. J. Newman, "An efficient and principled method for detecting communities in networks", arxiv:1104.3590
★Michael J. Barber, John W. Clark, "Detecting network communities by propagating labels under constraints", Physical Review E 80 (2009): 026129,arxiv:0903.3138
★Jonathan W. Berry, Bruce Hendrickson, Randall A. LaViolette, Cynthia A. Phillips, "Tolerating the Community Detection Resolution Limit with Edge Weighting", arxiv:0903.1072
[I have to say that their abstract sounds like a recipe for over-fitting, but I haven't read the paper so that could be totally unfair.]
★S. Boccaletti, M. Ivanchenko,V. Latora, A. Pluchino and A. Rapisarda, "Dynamical clustering methods to find community structures", physics/0607179
★Michael James Bommarito II, Daniel Martin Katz, Jon Zelner, "On the Stability of Community Detection Algorithms on Longitudinal Citation Data",arxiv:0908.0449
★U. Brandes, D. Delling, M. Gaertler, R. Goerke, M. Hoefer, Z. Nikoloski, and D. Wagner, "Maximizing Modularity is hard", physics/0608255 [i.e., maximizing Newman's Q is NP
hard. I haven't read beyond the abstract yet, so I don't know if they address the question of what makes it hard in the hard cases, and whether those are properties we should
expect to see in real-world networks. Conceivably, actual social networks are, on average, easy to modularize...]
★Andrea Capocci,Vito D. P. Servedio, Guido Caldarelli, Francesca Colaiori, "Detecting communities in large networks", cond-mat/0402499
★Horacio Castellini and Lilia Romanelli, "Social network from communities of electronic mail", nlin.CD/0509021
★Sanjeev Chauhan, Michelle Girvan and Edward Ott, "", Physical Review E 80(2009): 056114
★David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi, "Stochastic blockmodels with growing number of classes", arxiv:1011.4644
★Leon Danon, Albert Díaz-Guilera, and Alex Arenas, "The effect of size heterogeneity on community identification in complex networks", Journal of Statistical Mechanics:
Theory and Experiment (2006): P11010 =physics/0601144
★Leon Danon, Albert Díaz-Guilera, Jordi Duch and Alex Arenas, "Comparing community structure identification", Journal of Statistical Mechanics: Theory and Experiment
(2005): P09008 = cond-mat/0505245
★Bhaskar DasGupta, Devendra Desai, "On the Complexity of Newman's Community Finding Approach for Biological and Social Networks",arxiv:1102.0969
★Jordi Duch and Alex Arenas, "Community detection in complex networks using extremal optimization", Physical Review E 72 (2005): 027104
★Lilia Efimova and Stephanie Hendrick, "In search for a virtual settlement: An exploration of weblog community boundaries" [PDF reprint]
★Illes J. Farkas, Daniel Abel, Gergely Palla, Tamas Vicsek, "Weighted network modules", cond-mat/0703706
★S. Feldt, J. Waddell,V. L. Hetrick, J. D. Berke, and M. Zochowski, "Functional clustering algorithm for the analysis of dynamic network data",Physical Review E 79 (2009): 056104
★Daniel J. Fenn, Mason A. Porter, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamic communities in multichannel data: An application to the foreign
exchange market during the 2007--2008 credit crisis",arxiv:0811.3988
★Daniel J. Fenn, Mason A. Porter, Peter J. Mucha, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamical Clustering of Exchange Rates", arxiv:0905.4912
★Sam Field, Kenneth A. Frank, Kathryn Schiller, Catherine Riegle-Crumb and Chandra Muller, "Identifying positions from affiliation networks: Preserving the duality of people
and events", Social Networks 28 (2006): 97--123
★G. W. Flake, S. R. Lawrence, C. L. Giles and F. M. Coetzee, "Self-organization and identification of Web communities", IEEE Computer 36(2002): 66--71
★Santo Fortunato, "Community detection in graphs", arxiv:0906.0612
★Santo Fortunato and Marc Bathélemy, "Resolution limit in community detection", physics/0607100 = cite>Proceedings of the National Academy of Sciences (USA) 104 (2007):
36--41

★Yong-Yeol Ahn, James P. Bagrow and Sune Lehmann, "Link communities reveal multiscale complexity in networks", Nature 455 (2010): 761--764,arxiv:0903.3178 [Lehmann's
blog-post on this]
★Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing, "Mixed membership stochastic blockmodels", arxiv:0705.4485
★Nelson Augusto Alves, "Unveiling community structures in weighted networks", physics/0703087
★Leonardo Angelini, Stefano Boccaletti, Daniele Marinazzo, Mario Pellicoro, and Sebastiano Stramaglia, "Fast identification of network modules by optimization of ratio
association", cond-mat/0610182
★L. Angelini, D. Marinazzo, M. Pellicoro and S. Stramaglia, "Natural clustering: the modularity approach", cond-mat/0607643
★Alex Arenas, Javier Borge-Holthoefer, Sergio Gomez, Gorka Zamora-Lopez, "Optimal map of the modular structure of complex networks", New Journal of Physics 12 (2010):
053009, arxiv:0911.2651
★A. Arenas, J. Duch, A. Fernandez, S. Gomez, "Size reduction of complex networks preserving modularity", physics/0702015 [Do you really need all those links? Wouldn't your
life be simpler if you could just ignore some of them?]
★Alex Arenas, Alberto Fernandez, Sergio Gomez, "Multiple resolution of the modular structure of complex networks", physics/0703218
★Alex Arenas, Alberto Fernandez, Santo Fortunato, Sergio Gomez, "Motif-based communities in complex networks", arxiv:0710.0059
★Jim Bagrow and Erik Bollt, "A Local Method for Detecting Communities",cond-mat/0412482
★James Bagrow, Erik Bollt, Luciano da F. Costa, "Network Structure Revealed by Short Cycles", cond-mat/0612502
★Brian Ball, Brian Karrer, M. E. J. Newman, "An efficient and principled method for detecting communities in networks", arxiv:1104.3590

135 algorithms in
★Michael J. Barber, John W. Clark, "Detecting network communities by propagating labels under constraints", Physical Review E 80 (2009): 026129,arxiv:0903.3138
★Jonathan W. Berry, Bruce Hendrickson, Randall A. LaViolette, Cynthia A. Phillips, "Tolerating the Community Detection Resolution Limit with Edge Weighting", arxiv:0903.1072
[I have to say that their abstract sounds like a recipe for over-fitting, but I haven't read the paper so that could be totally unfair.]
★S. Boccaletti, M. Ivanchenko,V. Latora, A. Pluchino and A. Rapisarda, "Dynamical clustering methods to find community structures", physics/0607179

U. Michigan index
★Michael James Bommarito II, Daniel Martin Katz, Jon Zelner, "On the Stability of Community Detection Algorithms on Longitudinal Citation Data",arxiv:0908.0449
★U. Brandes, D. Delling, M. Gaertler, R. Goerke, M. Hoefer, Z. Nikoloski, and D. Wagner, "Maximizing Modularity is hard", physics/0608255 [i.e., maximizing Newman's Q is NP
hard. I haven't read beyond the abstract yet, so I don't know if they address the question of what makes it hard in the hard cases, and whether those are properties we should
expect to see in real-world networks. Conceivably, actual social networks are, on average, easy to modularize...]
★Andrea Capocci,Vito D. P. Servedio, Guido Caldarelli, Francesca Colaiori, "Detecting communities in large networks", cond-mat/0402499
★Horacio Castellini and Lilia Romanelli, "Social network from communities of electronic mail", nlin.CD/0509021
★Sanjeev Chauhan, Michelle Girvan and Edward Ott, "", Physical Review E 80(2009): 056114
★David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi, "Stochastic blockmodels with growing number of classes", arxiv:1011.4644
★Leon Danon, Albert Díaz-Guilera, and Alex Arenas, "The effect of size heterogeneity on community identification in complex networks", Journal of Statistical Mechanics:
Theory and Experiment (2006): P11010 =physics/0601144
★Leon Danon, Albert Díaz-Guilera, Jordi Duch and Alex Arenas, "Comparing community structure identification", Journal of Statistical Mechanics: Theory and Experiment
(2005): P09008 = cond-mat/0505245
★Bhaskar DasGupta, Devendra Desai, "On the Complexity of Newman's Community Finding Approach for Biological and Social Networks",arxiv:1102.0969
★Jordi Duch and Alex Arenas, "Community detection in complex networks using extremal optimization", Physical Review E 72 (2005): 027104
★Lilia Efimova and Stephanie Hendrick, "In search for a virtual settlement: An exploration of weblog community boundaries" [PDF reprint]
★Illes J. Farkas, Daniel Abel, Gergely Palla, Tamas Vicsek, "Weighted network modules", cond-mat/0703706
★S. Feldt, J. Waddell,V. L. Hetrick, J. D. Berke, and M. Zochowski, "Functional clustering algorithm for the analysis of dynamic network data",Physical Review E 79 (2009): 056104
★Daniel J. Fenn, Mason A. Porter, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamic communities in multichannel data: An application to the foreign
exchange market during the 2007--2008 credit crisis",arxiv:0811.3988
★Daniel J. Fenn, Mason A. Porter, Peter J. Mucha, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamical Clustering of Exchange Rates", arxiv:0905.4912
★Sam Field, Kenneth A. Frank, Kathryn Schiller, Catherine Riegle-Crumb and Chandra Muller, "Identifying positions from affiliation networks: Preserving the duality of people
and events", Social Networks 28 (2006): 97--123
★G. W. Flake, S. R. Lawrence, C. L. Giles and F. M. Coetzee, "Self-organization and identification of Web communities", IEEE Computer 36(2002): 66--71
★Santo Fortunato, "Community detection in graphs", arxiv:0906.0612
★Santo Fortunato and Marc Bathélemy, "Resolution limit in community detection", physics/0607100 = cite>Proceedings of the National Academy of Sciences (USA) 104 (2007):
36--41

What makes you different?



Computing reduced to
commercial limits



commercial limits

Allows overlapping
(1 person may be in 2 groups)



commercial limits

Allows overlapping
(1 person may be in 2 groups)

User interface
to help


Who are you?
Work Experience
• Current - PhD Candidate (@ UPM) (1st year)
• Research field: complex networks
• Published paper
• June 2011 - 1st IEEE Network Science Workshop, West
Point NY: "Generating scale-free networks with adjustable
clustering coefficient via random walks," doi: 10.1109/
NSW.2011.6004642
• 2008-09 International Board Member ( Treasurer & Industry
relations) of Electrical Engineering European Student
Association (EESTEC). Carlos Herrera
Education Age 25
• 2010 - MoS in Electrical Engineering ( Telecommunications) @ Universidad Politécnica de Madrid
• 2011 - Master in Statical-Computational Information Treatment @ Complutense U. of Madrid
• Accepted for a research stay @ MIT with professor M. Gonzalez
Awards
• Scholarships for Academic Excellence years 2004 and 2005 provided by Madrid Region
Government. (700 scholarship among 200K eligible candidates)

@findyourcircles

Who are you?
Work Experience
• Software Engineer @Geographica Spatial
• Lead software analyst since May 2011
• GIS Software develpment
• Mobile and web software developement
• System administrator @ CMU San Juan
• Computer networks (LARTC, Load Balancing)
• Virtualization (Xen)
• IT Services management FTP, NFS, LVM, PAM-SQL
Education Alberto Asuero
• MoS in Computer Science, Age 25
• Universidad Autonóma de Madrd & University of Applied
Sciences of Western Switzerland (HEIG-VD)

Technical Skills

@ﬁndyourcircles

How does it looks like?

@ﬁndyourcircles


You can try a proof of concept in ﬁndyourcircles.com

Text


IDEA DEVELOPMENT

FYC proof of concept only evaluates
friendship links, but could be applied to
any social graph which can be deﬁned
among users (tagged pictures, events
attended...)


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