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   Barry Wellman
  _______________________________________________________________________
   FRSC               Co-Director NetLab Network           INSNA Founder
   University of Toronto                                  Toronto Canada
                        Lim Chong Yah Professor
   Dept of Communication and New Media  National University of Singapore
   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
                  Old/NewCyberTimes http://bit.ly/c8N9V8
   _______________________________________________________________________


Co-evolutionary Dynamics of Collective Action with Signaling for a Quorum

    From humans to social insects and bacteria, decision-making is often influenced by some form of collective signaling, be it quorum, information exchange, pledges or announcements. Here we investigate how such signaling systems evolve when collective action entails a public good, and how meanings co-evolve with individual choices, given Nature˙˙s most prevalent states. We find a rich scenario, showing how natural selection is able to evolve a costly quorum signaling system that allows individuals to coordinate their action so as to provide the appropriate response to different states of Nature. We show that signaling robustly and selectively promotes cooperative collective action when coordinated action is most needed. In light of our results, and despite the complexity that collective action relying on quorum signaling may entail, it is not so surprising how signaling is a ubiquitous property of the living world.

Pacheco JM, Vasconcelos VV, Santos FC, Skyrms B (2015) Co-evolutionary Dynamics of Collective Action with Signaling for a Quorum. PLoS Comput Biol 11(2): e1004101. http://dx.doi.org/10.1371/journal.pcbi.1004101 ;

See it on Scoop.it (http://www.scoop.it/t/papers/p/4039034120/2015/03/14/co-evolutionary-dynamics-of-collective-action-with-signaling-for-a-quorum) , via Papers (http://www.scoop.it/t/papers)



Attention decay in science

    The exponential growth in the number of scientific papers makes it increasingly difficult for researchers to keep track of all the publications relevant to their work. Consequently, the attention that can be devoted to individual papers, measured by their citation counts, is bound to decay rapidly. In this work we make a thorough study of the life-cycle of papers in different disciplines. Typically, the citation rate of a paper increases up to a few years after its publication, reaches a peak and then decreases rapidly. This decay can be described by an exponential or a power law behavior, as in ultradiffusive processes, with exponential fitting better than power law for the majority of cases. The decay is also becoming faster over the years, signaling that nowadays papers are forgotten more quickly. However, when time is counted in terms of the number of published papers, the rate of decay of citations is fairly independent of the period considered. This indicates that the
attention of scholars depends on the number of published items, and not on real time.

Attention decay in science
Pietro Della Briotta Parolo, Raj Kumar Pan, Rumi Ghosh, Bernardo A. Huberman, Kimmo Kaski, Santo Fortunato

http://arxiv.org/abs/1503.01881

See it on Scoop.it (http://www.scoop.it/t/papers/p/4039034190/2015/03/14/attention-decay-in-science) , via Papers (http://www.scoop.it/t/papers)



Modeling infectious disease dynamics in the complex landscape of global health

    Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for
decision-making in global health.

Modeling infectious disease dynamics in the complex landscape of global health
Hans Heesterbeek, et al.

Science 13 March 2015:
Vol. 347 no. 6227
http://dx.doi.org/10.1126/science.aaa4339 ;

See it on Scoop.it (http://www.scoop.it/t/papers/p/4039095643/2015/03/13/modeling-infectious-disease-dynamics-in-the-complex-landscape-of-global-health) , via Papers (http://www.scoop.it/t/papers)


Predicting Epidemic Risk from Past Temporal Contact Data

    Following the emergence of a transmissible disease epidemic, interventions and resources need to be prioritized to efficiently control its spread. While the knowledge of the pattern of disease-transmission contacts among hosts would be ideal for this task, the continuously changing nature of such pattern makes its use less practical in real public health emergencies (or otherwise highly resource-demanding when possible). We show that in such situations critical knowledge to assess the real-time risk of infection can be extracted from past temporal contact data. An index expressing the conservation of contacts over time is proposed as an effective tool to prioritize interventions, and its efficiency is tested considering real data on livestock movements and on human sexual encounters.

Valdano E, Poletto C, Giovannini A, Palma D, Savini L, et al. (2015) Predicting Epidemic Risk from Past Temporal Contact Data. PLoS Comput Biol 11(3): e1004152. http://dx.doi.org/10.1371/journal.pcbi.1004152 ;

See it on Scoop.it (http://www.scoop.it/t/papers/p/4039079280/2015/03/13/predicting-epidemic-risk-from-past-temporal-contact-data) , via Papers (http://www.scoop.it/t/papers)



The Evolution of Popular Music: USA 1960-2010

    In modern societies, cultural change seems ceaseless. The flux of 
fashion is especially obvious for popular music. While much has been 
written about the origin and evolution of pop, most claims about its 
history are anecdotal rather than scientific in nature. To rectify this we 
investigate the US Billboard Hot 100 between 1960 and 2010. Using Music 
Information Retrieval (MIR) and text-mining tools we analyse the musical 
properties of ~17,000 recordings that appeared in the charts and 
demonstrate quantitative trends in their harmonic and timbral properties. 
We then use these properties to produce an audio-based classification of 
musical styles and study the evolution of musical diversity and disparity, 
testing, and rejecting, several classical theories of cultural change. 
Finally, we investigate whether pop musical evolution has been gradual or 
punctuated. We show that, although pop music has evolved continuously, it 
did so with particular rapidity during three stylistic "revolutions" 
around 1964, 1983 and 1991. We conclude by discussing how our study points 
the way to a quantitative science of cultural change.

The Evolution of Popular Music: USA 1960-2010
Matthias Mauch, Robert M. MacCallum, Mark Levy, Armand M. Leroi

http://arxiv.org/abs/1502.05417

See it on Scoop.it (http://www.scoop.it/t/papers/p/4039032839/2015/03/13/the-evolution-of-popular-music-usa-1960-2010) , via Papers (http://www.scoop.it/t/papers)


Daily rhythms in mobile telephone communication

    Circadian rhythms are known to be important drivers of human activity 
and the recent availability of electronic records of human behaviour has 
provided fine-grained data of temporal patterns of activity on a large 
scale. Further, questionnaire studies have identified important individual 
differences in circadian rhythms, with people broadly categorised into 
morning-like or evening-like individuals. However, little is known about 
the social aspects of these circadian rhythms, or how they vary across 
individuals. In this study we use a unique 18-month dataset that combines 
mobile phone calls and questionnaire data to examine individual 
differences in the daily rhythms of mobile phone activity. We demonstrate 
clear individual differences in daily patterns of phone calls, and show 
that these individual differences are persistent despite a high degree of 
turnover in the individuals' social networks. Further, women's calls were 
longer than men's calls, especially during the evening and at night, and 
these calls were typically focused on a small number of emotionally 
intense relationships. These results demonstrate that individual 
differences in circadian rhythms are not just related to broad patterns of 
morningness and eveningness, but have a strong social component, in 
directing phone calls to specific individuals at specific times of day.

Daily rhythms in mobile telephone communication

Talayeh Aledavood, Eduardo López, Sam G. B. Roberts, Felix Reed-Tsochas, Esteban Moro, Robin I. M. Dunbar, Jari Saramäki

http://arxiv.org/abs/1502.06866

See it on Scoop.it (http://www.scoop.it/t/papers/p/4039031590/2015/03/12/daily-rhythms-in-mobile-telephone-communication) , via Papers (http://www.scoop.it/t/papers)


Fundamentals of Complex Networks: Models, Structures and Dynamics (by  Guanrong Chen et al.)

    Complex networks such as the Internet, transportation networks, power grids, biological neural networks, and scientific cooperation networks of all kinds provide challenges for future technological development.

˙˙ The first systematic presentation of dynamical evolving networks, with many up-to-date applications and homework projects to enhance study
˙˙ Complex networks are becoming an increasingly important area of research
˙˙ Presented in a logical, constructive style, from basic through to complex, examining algorithms, through to construct networks and research challenges of the future


See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4038659146/2015/03/12/fundamentals-of-complex-networks-models-structures-and-dynamics-by-guanrong-chen-et-al) , via CxBooks (http://www.scoop.it/t/cxbooks)


Disaster Theory: An Interdisciplinary Approach to Concepts and Causes (by David Etkin)

    Disaster Theory: An Interdisciplinary Approach to Concepts and Causes offers the theoretical background needed to understand what disasters are and why they occur. Drawing on related disciplines, including sociology, risk theory, and seminal research on disasters and emergency management, Disaster Theory clearly lays out the conceptual framework of the emerging field of disaster studies. Tailored to the needs of advanced undergraduates and graduate students, this unique text also provides an ideal capstone for students who have already been introduced to the fundamentals of emergency management. Disaster Theory emphasizes the application of critical thinking in understanding disasters and their causes by synthesizing a wide range of information on theory and practice, including input from leading scholars in the field.
* Offers the first cohesive depiction of disaster theory
* Incorporates material from leading thinkers in the field, as well as student exercises and critical thinking questions, making this a rich resource for advanced courses
* Written from an international perspective and includes case studies of disasters and hazards from around the world for comparing the leading models of emergency response
* Challenges the reader to think critically about important questions in disaster management from various points of view



See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4038659177/2015/03/11/disaster-theory-an-interdisciplinary-approach-to-concepts-and-causes-by-david-etkin) , via CxBooks (http://www.scoop.it/t/cxbooks)



Place and Health as Complex Systems: A Case Study and Empirical Test (by Brian Castellani et al.)

    The history of public health has focused on direct relationships between problems and solutions: vaccinations against diseases, ad campaigns targeting risky behaviors. But the accelerating pace and mounting intricacies of our lives are challenging the field to find new scientific methods for studying community health. The complexities of place (COP) approach is emerging as one such promising method.


Place and Health as Complex Systems demonstrates how COP works, making an empirical case for its use in for designing and implementing interventions. This brief resource reviews the defining characteristics of places as dynamic and evolving social systems, rigorously testing them as well as the COP approach itself. The study, of twenty communities within one county in the Midwest, combines case-based methods and complexity science to determine whether COP improves upon traditional statistical methods of public health research. Its conclusions reveal strengths and limitations of the approach, immediate possibilities for its use, and challenges regarding future research. Included in the coverage:


* Characteristics of places and the complexities of place approach.
* The Definitional Test of Complex Systems.
* Case-based modeling using the SACS toolkit.
* Methods, maps, and measures used in the study.
* Places as nodes within larger networks.
* Places as power-based conflicted negotiations.




See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4038660008/2015/03/11/place-and-health-as-complex-systems-a-case-study-and-empirical-test-by-brian-castellani-et-al) , via CxBooks (http://www.scoop.it/t/cxbooks)



Network Science Book

    The power of network science,
the beauty of network visualization.
Network Science, a textbook for network science, is freely available under the Creative Commons licence. Follow its development on Facebook, Twitter or by signining up to our mailing list, so that we can notify you of new chapters and developments.
The book is the result of a collaboration between a number of individuals, shaping everything, from content (Albert-László Barabási), to visualizations and interactive tools (Gabriele Musella, Mauro Martino, Nicole Samay, Kim Albrecht), simulations and data analysis (Márton Pósfai). The printed version of the book will be published by Cambridge University Press in 2015. In the coming months the website will be expanded with an interactive version of the text, datasets, and slides to teach the material.

http://barabasi.com/networksciencebook/

See it on Scoop.it (http://www.scoop.it/t/cxbooks/p/4038953009/2015/03/11/network-science-book) , via CxBooks (http://www.scoop.it/t/cxbooks)



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

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