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SOCNET  May 2015

SOCNET May 2015

Subject:

Selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 11 May 2015 10:05:07 -0400

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (124 lines)

***** 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, 11 May 2015 11:04:01 +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://comdig.unam.mx?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033


A multilevel multimodal circuit enhances action selection in Drosophila

    Natural events present multiple types of sensory cues, each detected by a specialized sensory modality. Combining information from several modalities is essential for the selection of appropriate actions. Key to understanding multimodal computations is determining the structural patterns of multimodal convergence and how these patterns contribute to behaviour. Modalities could converge early, late or at multiple levels in the sensory processing hierarchy. Here we show that combining mechanosensory and nociceptive cues synergistically enhances the selection of the fastest mode of escape locomotion in Drosophila larvae. In an electron microscopy volume that spans the entire insect nervous system, we reconstructed the multisensory circuit supporting the synergy, spanning multiple levels of the sensory processing hierarchy. The wiring diagram revealed a complex multilevel multimodal convergence architecture. Using behavioural and physiological studies, we identified functionally
connected circuit nodes that trigger the fastest locomotor mode, and others that facilitate it, and we provide evidence that multiple levels of multimodal integration contribute to escape mode selection. We propose that the multilevel multimodal convergence architecture may be a general feature of multisensory circuits enabling complex input˙˙output functions and selective tuning to ecologically relevant combinations of cues.

A multilevel multimodal circuit enhances action selection in Drosophila
˙˙ Tomoko Ohyama, Casey M. Schneider-Mizell, Richard D. Fetter, Javier Valdes Aleman, Romain Franconville, Marta Rivera-Alba, Brett D. Mensh, Kristin M. Branson, Julie H. Simpson, James W. Truman, Albert Cardona & Marta Zlatic

Nature 520, 633˙˙639 (30 April 2015) http://dx.doi.org/10.1038/nature14297?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033

See it on Scoop.it (http://www.scoop.it/t/papers/p/4043016775/2015/05/06/a-multilevel-multimodal-circuit-enhances-action-selection-in-drosophila?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033) , via Papers (http://www.scoop.it/t/papers?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033)


Hierarchical organisation of Britain through percolation theory

    Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations, which are the outcome of geographical, political and historical constraints. Using percolation theory on the street intersections and on the road network of Britain, we obtain hierarchies at different scales that are independent of administrative arrangements. Natural boundaries, such as islands and National Parks, consistently emerge at the largest/regional scales. Cities are devised through recursive percolations on each of the emerging clusters, but the system does not undergo a phase transition at the distance threshold at which cities can be defined. This specific distance is obtained by computing the fractal dimension of the clusters extracted at each distance threshold. We observe that the fractal dimension presents a maximum over all the different distance thresholds. The clusters obtained at this maximum are in very good correspondence
to the morphological definition of cities given by satellite images, and by other methods previously developed by the authors (Arcaute et al. 2015).

Hierarchical organisation of Britain through percolation theory
Elsa Arcaute, Carlos Molinero, Erez Hatna, Roberto Murcio, Camilo Vargas-Ruiz, Paolo Masucci, Jiaqiu Wang, Michael Batty

http://arxiv.org/abs/1504.08318?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033

See it on Scoop.it (http://www.scoop.it/t/papers/p/4042845394/2015/05/05/hierarchical-organisation-of-britain-through-percolation-theory?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033) , via Papers (http://www.scoop.it/t/papers?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033)



Ranking in interconnected multilayer networks reveals versatile nodes

    The determination of the most central agents in complex networks is important because they are responsible for a faster propagation of information, epidemics, failures and congestion, among others. A challenging problem is to identify them in networked systems characterized by different types of interactions, forming interconnected multilayer networks. Here we describe a mathematical framework that allows us to calculate centrality in such networks and rank nodes accordingly, finding the ones that play the most central roles in the cohesion of the whole structure, bridging together different types of relations. These nodes are the most versatile in the multilayer network. We investigate empirical interconnected multilayer networks and show that the approaches based on aggregating˙˙or neglecting˙˙the multilayer structure lead to a wrong identification of the most versatile nodes, overestimating the importance of more marginal agents and demonstrating the power of versatility in
predicting their role in diffusive and congestion processes.

Ranking in interconnected multilayer networks reveals versatile nodes
Manlio De Domenico, Albert Solé-Ribalta, Elisa Omodei, Sergio Gómez & Alex Arenas

Nature Communications 6, Article number: 6868 http://dx.doi.org/10.1038/ncomms7868?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033 ;

See it on Scoop.it (http://www.scoop.it/t/papers/p/4042910436/2015/05/05/ranking-in-interconnected-multilayer-networks-reveals-versatile-nodes?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033) , via Papers (http://www.scoop.it/t/papers?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033)



Unveiling patterns of international communities in a global city using mobile phone data

    We analyse a large mobile phone activity dataset provided by Telecom Italia for the Telecom Big Data Challenge contest. The dataset reports the international country codes of every call/SMS made and received by mobile phone users in Milan, Italy, between November and December 2013, with a spatial resolution of about 200 meters. We first show that the observed spatial distribution of international codes well matches the distribution of international communities reported by official statistics, confirming the value of mobile phone data for demographic research. Next, we define an entropy function to measure the heterogeneity of the international phone activity in space and time. By comparing the entropy function to empirical data, we show that it can be used to identify the city˙˙s hotspots, defined by the presence of points of interests. Eventually, we use the entropy function to characterize the spatial distribution of international communities in the city. Adopting a
topological data analysis approach, we find that international mobile phone users exhibit some robust clustering patterns that correlate with basic socio-economic variables. Our results suggest that mobile phone records can be used in conjunction with topological data analysis tools to study the geography of migrant communities in a global city.

Unveiling patterns of international communities in a global city using mobile phone data
Paolo Bajardi, Matteo Delfino, André Panisson, Giovanni Petri and Michele Tizzoni

EPJ Data Science 2015, 4:3 http://dx.doi.org/10.1140/epjds/s13688-015-0041-5?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033 ;

See it on Scoop.it (http://www.scoop.it/t/papers/p/4042906009/2015/05/05/unveiling-patterns-of-international-communities-in-a-global-city-using-mobile-phone-data?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033) , via Papers (http://www.scoop.it/t/papers?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033)



A set of measures to quantify the dynamicity of longitudinal social networks

    This study proposes a new set of measures for longitudinal social networks (LSNs). A LSN evolves over time through the creation and/or deletion of links among a set of actors (e.g., individuals or organizations). The current literature does feature some methods, such as multiagent simulation models, for studying the dynamics of LSNs. These methods have mainly been utilized to explore evolutionary changes in LSNs from one state to another and to explain the underlying mechanisms for these changes. However, they cannot quantify different aspects of a LSN. For example, these methods are unable to quantify the level of dynamicity shown by an actor in a LSN and its contribution to the overall dynamicity shown by that LSN. This article develops a set of measures for LSNs to overcome this limitation. We illustrate the benefits of these measures by applying them to an exploration of the Enron crisis. These measures successfully identify a significant but previously unobserved change
in network structures (both at individual and group levels) during Enron's crisis period.

A set of measures to quantify the dynamicity of longitudinal social networks
Shahadat Uddin, Arif Khan andMahendra Piraveenan

Complexity
Early View

http://dx.doi.org/10.1002/cplx.21690?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033

See it on Scoop.it (http://www.scoop.it/t/papers/p/4042903143/2015/05/05/a-set-of-measures-to-quantify-the-dynamicity-of-longitudinal-social-networks?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033) , via Papers (http://www.scoop.it/t/papers?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033)



Making 20th Century Science: How Theories Became Knowledge (by Stephen G. Brush)

    Historically, the scientific method has been said to require proposing a theory, making a prediction of something not already known, testing the prediction, and giving up the theory (or substantially changing it) if it fails the test. A theory that leads to several successful predictions is more likely to be accepted than one that only explains what is already known but not understood. This process is widely treated as the conventional method of achieving scientific progress, and was used throughout the twentieth century as the standard route to discovery and experimentation.
But does science really work this way? In Making 20th Century Science, Stephen G. Brush discusses this question, as it relates to the development of science throughout the last century. Answering this question requires both a philosophically and historically scientific approach, and Brush blends the two in order to take a close look at how scientific methodology has developed. Several cases from the history of modern physical and biological science are examined, including Mendeleev's Periodic Law, Kekule's structure for benzene, the light-quantum hypothesis, quantum mechanics, chromosome theory, and natural selection. In general it is found that theories are accepted for a combination of successful predictions and better explanations of old facts.
Making 20th Century Science is a large-scale historical look at the implementation of the scientific method, and how scientific theories come to be accepted.



See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4042635535/2015/05/04/making-20th-century-science-how-theories-became-knowledge-by-stephen-g-brush?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033) , via CxBooks (http://www.scoop.it/t/cxbooks?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033)


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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://www.scoop.it/u/complexity-digest?utm_source=Complexity+Digest&utm_campaign=faaf383814-RSS_EMAIL_CAMPAIGN&utm_medium=email&utm_term=0_f55ea67de1-faaf383814-67211033 ) and using the "Suggest" button.
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