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   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
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---------- Forwarded message ----------
Date: Mon, 21 Sep 2015 11:03:14 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
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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=6dbe9c7a0d&e=55e25a0e3e



Visualizing signatures of human activity in cities across the globe

    The availability of big data on human activity is currently changing the way we look at our surroundings. With the high penetration of mobile phones, nearly everyone is already carrying a high-precision sensor providing an opportunity to monitor and analyze the dynamics of human movement on unprecedented scales. In this article, we present a technique and visualization tool which uses aggregated activity measures of mobile networks to gain information about human activity shaping the structure of the cities. Based on ten months of mobile network data, activity patterns can be compared through time and space to unravel the "city's pulse" as seen through the specific signatures of different locations. Furthermore, the tool allows classifying the neighborhoods into functional clusters based on the timeline of human activity, providing valuable insights on the actual land use patterns within the city. This way, the approach and the tool provide new ways of looking at the city
structure from historical perspective and potentially also in real-time based on dynamic up-to-date records of human behavior. The online tool presents results for four global cities: New York, London, Hong Kong and Los Angeles.

Visualizing signatures of human activity in cities across the globe
Dániel Kondor, Pierrick Thebault, Sebastian Grauwin, István Gódor, Simon Moritz, Stanislav Sobolevsky, Carlo Ratti

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Dynamics of deceptive interactions in social networks

    In this paper we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion, and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and in this sense they have substantial centrality in the network. We then discuss the consequences of
these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society.

Dynamics of deceptive interactions in social networks
Rafael A. Barrio, Tzipe Govezensky, Robin Dunbar, Gerardo Ińiguez, Kimmo Kaski

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Quantifying the impact of weak, strong, and super ties in scientific careers

    Scientists are frequently faced with the important decision to start or terminate a creative partnership. This process can be influenced by strategic motivations, as early career researchers are pursuers, whereas senior researchers are typically attractors, of new collaborative opportunities. Focusing on the longitudinal aspects of scientific collaboration, we analyzed 473 collaboration profiles using an ego-centric perspective which accounts for researcher-specific characteristics and provides insight into a range of topics, from career achievement and sustainability to team dynamics and efficiency. From more than 166,000 collaboration records, we quantify the frequency distributions of collaboration duration and tie-strength, showing that collaboration networks are dominated by weak ties characterized by high turnover rates. We use analytic extreme-value thresholds to identify a new class of indispensable `super ties', the strongest of which commonly exhibit >50%
publication overlap with the central scientist. The prevalence of super ties suggests that they arise from career strategies based upon cost, risk, and reward sharing and complementary skill matching. We then use a combination of descriptive and panel regression methods to compare the subset of publications coauthored with a super tie to the subset without one, controlling for pertinent features such as career age, prestige, team size, and prior group experience. We find that super ties contribute to above-average productivity and a 17% citation increase per publication, thus identifying these partnerships - the analog of life partners - as a major factor in science career development.

Quantifying the impact of weak, strong, and super ties in scientific careers
Alexander Michael Petersen

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Do we need another coffee house? The amenity space and the evolution of neighborhoods

    Neighborhoods populated by amenities, such as restaurants, cafes, and libraries, are considered to be a key property of desirable cities. Yet, despite the global enthusiasm for amenity-rich neighborhoods, little is known about the empirical laws governing the colocation of amenities at the neighborhood scale. Here, we contribute to our understanding of the naturally occurring neighborhood-scale agglomerations of amenities observed in cities by using a dataset summarizing the precise location of millions of amenities. We use this dataset to build the network of co-location of amenities, or Amenity Space, by first introducing a clustering algorithm to identify neighborhoods, and then using the identified neighborhoods to map the probability that two amenities will be co-located in one of them. Finally, we use the Amenity Space to build a recommender system that identifies the amenities that are missing in a neighborhood given its current pattern of specialization. This opens
the door for the construction of amenity recommendation algorithms that can be used to evaluate neighborhoods and inform their improvement and development.

Do we need another coffee house? The amenity space and the evolution of neighborhoods
César A. Hidalgo, Elisa E. Castańer

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Large-scale analysis of Zipf's law in English texts

    Despite being a paradigm of quantitative linguistics, Zipf's law for words suffers from three main problems: its formulation is ambiguous, its validity has not been tested rigorously from a statistical point of view, and it has not been confronted to a representatively large number of texts. So, we can summarize the current support of Zipf's law in texts as anecdotic.
We try to solve these issues by studying three different versions of Zipf's law and fitting them to all available English texts in the Project Gutenberg database (consisting of more than 30000 texts). To do so we use state-of-the art tools in fitting and goodness-of-fit tests, carefully tailored to the peculiarities of text statistics. Remarkably, one of the three versions of Zipf's law, consisting of a pure power-law form in the complementary cumulative distribution function of word frequencies, is able to fit more than 40% of the texts in the database (at the 0.05 significance level), for the whole domain of frequencies (from 1 to the maximum value) and with only one free parameter (the exponent).

Large-scale analysis of Zipf's law in English texts
Isabel Moreno-Sánchez, Francesc Font-Clos, Álvaro Corral

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Controling contagious processes on temporal networks via adaptive rewiring

    We consider recurrent contagious processes on a time-varying network. As a control procedure to mitigate the epidemic, we propose an adaptive rewiring mechanism for temporary isolation of infected nodes upon their detection. As a case study, we investigate the network of pig trade in Germany. Based on extensive numerical simulations for a wide range of parameters, we demonstrate that the adaptation mechanism leads to a significant extension of the parameter range, for which most of the index nodes (origins of the epidemic) lead to vanishing epidemics. We find that diseases with detection times around a week and infectious periods up to 3 months can be effectively controlled. Furthermore the performance of adaptation is very heterogeneous with respect to the index node. We identify index nodes that are most responsive to the adaptation strategy and quantify the success of the proposed adaptation scheme in dependence on the infectious period and detection times.

Controling contagious processes on temporal networks via adaptive rewiring
Vitaly Belik, Florian Fiebig, Philipp Hövel

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The End of Absence: Reclaiming What We˙˙ve Lost in a World of Constant Connection (by Michael Harris)

    Soon enough, nobody will remember life before the Internet. What does this unavoidable fact mean? Those of us who have lived both with and without the crowded connectivity of online life have a rare opportunity. We can still recognize the difference between Before and After. We catch ourselves idly reaching for our phones at the bus stop. Or we notice how, midconversation, a fumbling friend dives into the perfect recall of Google. In this eloquent and thought-provoking book, Michael Harris argues that amid all the changes we're experiencing, the most interesting is the end of absence-the loss of lack. The daydreaming silences in our lives are filled; the burning solitudes are extinguished. There's no true "free time" when you carry a smartphone. Today's rarest commodity is the chance to be alone with your thoughts.



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Collective dynamics of belief evolution under cognitive coherence and social conformity

    Human history has been marked by social instability and conflict, often driven by the irreconcilability of opposing sets of beliefs, ideologies, and religious dogmas. The dynamics of belief systems has been studied mainly from two distinct perspectives, namely how cognitive biases lead to individual belief rigidity and how social influence leads to social conformity. Here we propose a unifying framework that connects cognitive and social forces together in order to study the dynamics of societal belief evolution. Each individual is endowed with a network of interacting beliefs that evolves through interaction with other individuals in a social network. The adoption of beliefs is affected by both internal coherence and social conformity. Our framework explains how social instabilities can arise in otherwise homogeneous populations, how small numbers of zealots with highly coherent beliefs can overturn societal consensus, and how belief rigidity protects fringe groups and cults
against invasion from mainstream beliefs, allowing them to persist and even thrive in larger societies. Our results suggest that strong consensus may be insufficient to guarantee social stability, that the cognitive coherence of belief-systems is vital in determining their ability to spread, and that coherent belief-systems may pose a serious problem for resolving social polarization, due to their ability to prevent consensus even under high levels of social exposure. We therefore argue that the inclusion of cognitive factors into a social model is crucial in providing a more complete picture of collective human dynamics.

Collective dynamics of belief evolution under cognitive coherence and social conformity
Nathaniel Rodriguez, Johan Bollen, Yong-Yeol Ahn

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Competitive dynamics between criminals and law enforcement explains the super-linear scaling of crime in cities

    While cities have been the engine for innovation and growth for many millennia, they have also endured disproportionately more crime than smaller cities. Similarly to other urban sociological quantities, such as income, gross domestic product (GDP) and number of granted patents, it has been observed that crime scales super-linearly with city size. The default assumption is that super-linear scaling of crime, like other urban attributes, derives from agglomerative effects (that is, increasing returns from potentially more productive connections among criminals). However, crime initiation appears to be generated linearly with the population of a city, and the number of law enforcement officials scales sublinearly with city population. We hypothesize that the observed scaling exponent for net crime in a city is the result of competing dynamics between criminals and law enforcement, each with different scaling exponents, and where criminals win in the numbers game. We propose a
simple dynamical model able to accommodate these empirical observations, as well as the potential multiple scaling regimes emerging from the competitive dynamics between crime and law enforcement. Our model is also general enough to be able to correctly account for crime in universities, where university crime does not scale super-linearly, but linearly with enrolment size.

Competitive dynamics between criminals and law enforcement explains the super-linear scaling of crime in cities
Soumya Banerjee, Pascal Van Hentenryck & Manuel Cebrian

Palgrave Communications 1, Article number: 15022 (2015) http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=af5d2d5563&e=55e25a0e3e

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Complex networks: theory, methods and applications | Lake Como School of Advanced Studies

    Many real systems can be modeled as networks, where the elements of the system are nodes and interactions between elements are edges. An even larger set of systems can be modeled using dynamical processes on networks, which are in turn affected by the dynamics. Networks thus represent the backbone of many complex systems, and their theoretical and computational analysis makes it possible to gain insights into numerous applications. Networks permeate almost every conceivable discipline ˙˙including sociology, transportation, economics and finance, biology, and myriad others ˙˙ and the study of ˙˙network science˙˙ has thus become a crucial component of modern scientific education.
The school ˙˙Complex Networks: Theory, Methods, and Applications˙˙ offers a succinct education in network science. It is open to all aspiring scholars in any area of science or engineering who wish to study networks of any kind (whether theoretical or applied), and it is especially addressed to doctoral students and young postdoctoral scholars. The aim of the school is to deepen into both theoretical developments and applications in targeted fields.

Complex networks: theory, methods and applications
Lake Como School of Advanced Studies

Villa del Grumello, Como, Italy, 16-20 May 2016

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