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Chanukah is over. I don't know what else to do for the rest of the month, 
except read some of these selected papers

   Barry Wellman

   Step by step, link by link, putting it together--Streisand/Sondheim
        The earth to be spannd, connected by network--Walt Whitman
              It's Always Something--Roseanne Roseannadanna

              A day like all days, filled with those events
          that alter and illuminate our times--Walter Cronkite
   NetLab Network      			                            FRSC
   Distinguished Visiting Scholar   Social Media Lab   Ryerson University
         Founder, International Network for Social Network Analysis
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman  

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Date: Mon, 10 Dec 2018 12:05:48 +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

Conference on Complex Systems 2019

The Conference on Complex Systems (CCS) is the biggest and most important annual meeting of the international complex systems community. It comes under the auspices of the Complex Systems Society. Since its inception in 2004, CCS had always been Europe-based, but in 2015 & 2017, it moved to North & Latin America respectively.

In 2019, CCS will come to Asia for the first time. Held in Singapore at Nanyang Technological University, it promises an intellectually stimulating experience to be matched by an equally exciting social programme. ˙˙

Source: (

A structural transition in physical networks

In many physical networks, including neurons in the brain1,2, three-dimensional integrated circuits3 and underground hyphal networks4, the nodes and links are physical objects that cannot intersect or overlap with each other. To take this into account, non-crossing conditions can be imposed to constrain the geometry of networks, which consequently affects how they form, evolve and function. However, these constraints are not included in the theoretical frameworks that are currently used to characterize real networks5,6,7. Most tools for laying out networks are variants of the force-directed layout algorithm8,9˙˙which assumes dimensionless nodes and links˙˙and are therefore unable to reveal the geometry of densely packed physical networks. Here we develop a modelling framework that accounts for the physical sizes of nodes and links, allowing us to explore how non-crossing conditions affect the geometry of a network. For small link thicknesses, we observe a weakly interacting
regime in which link crossings are avoided via local link rearrangements, without altering the overall geometry of the layout compared to the force-directed layout. Once the link thickness exceeds a threshold, a strongly interacting regime emerges in which multiple geometric quantities, such as the total link length and the link curvature, scale with the link thickness. We show that the crossover between the two regimes is driven by the non-crossing condition, which allows us to derive the transition point analytically and show that networks with large numbers of nodes will ultimately exist in the strongly interacting regime. We also find that networks in the weakly interacting regime display a solid-like response to stress, whereas in the strongly interacting regime they behave in a gel-like fashion. Networks in the weakly interacting regime are amenable to 3D printing and so can be used to visualize network geometry, and the strongly interacting regime provides insights
into the scaling of the sizes of densely packed mammalian brains.

A structural transition in physical networks
Nima Dehmamy, Soodabeh Milanlouei & Albert-László Barabási
Nature volume 563, pages 676˙˙680 (2018)

Source: (

The Impact of Potential Crowd Behaviours on Emergency Evacuation

    Crowd dynamics have important applications in evacuation management systems relevant to organizing safer large scale gatherings. For crowd safety, it is very important to study the evolution of potential crowd behaviours by simulating the crowd evacuation process. Planning crowd control tasks via studying the impact of crowd behavioural evolution towards evacuation simulation could mitigate the possibility of crowd disasters that may happen. During a typical emergency evacuation scenario, conflict among agents occurs when agents intend to move to the same location as a result of the interaction of agents within their nearest neighbours. The effect of the agent response towards their neighbourhood is vital in order to understand the effect of variation of crowd behaviours towards the whole environment. In this work, we model crowd motion subject to exit congestion under uncertainty conditions in a continuous space via computer simulations. We model best-response, risk-seeking,
risk-averse and risk-neutral behaviours of agents via certain game theory notions. We perform computer simulations with heterogeneous populations in order to study the effect of the evolution of agent behaviours towards egress flow under threat conditions. Our simulation results show the relation between the local crowd pressure and the number of injured agents. We observe that when the proportion of agents in a population of risk-seeking agents is increased, the average crowd pressure, average local density and the number of injured agents get increased. Besides that, based on our simulation results, we can infer that crowd disaster could be prevented if the agent population are full of risk-averse and risk-neutral agents despite circumstances that lead to threat consequences.

The Impact of Potential Crowd Behaviours on Emergency Evacuation: An Evolutionary Game Theoretic Approach
Azhar Mohd Ibrahim , Ibrahim Venkat and De Wilde Philippe
Journal of Artificial Societies and Social Simulation 22 (1) 3>
DOI: 10.18564/jasss.3837

Source: (

Quantifying the sensing power of crowd-sourced vehicle fleets

    Sensors can measure air quality, traffic congestion, and other aspects of urban environments. The fine-grained diagnostic information they provide could help urban managers to monitor a city's health. Recently, a `drive-by' paradigm has been proposed in which sensors are deployed on third-party vehicles, enabling wide coverage at low cost} Research on drive-by sensing has mostly focused on sensor engineering, but a key question remains unexplored: How many vehicles would be required to adequately scan a city? Here, we address this question by analyzing the sensing power of a taxi fleet. Taxis, being numerous in cities and typically equipped with some sensing technology (e.g. GPS), are natural hosts for the sensors. Our strategy is to view drive-by sensing as a spreading process, in which the area of sensed terrain expands as sensor-equipped taxis diffuse through a city's streets. In tandem with a simple model for the movements of the taxis, this analogy lets us analytically
determine the fraction of a city's street network sensed by a fleet of taxis during a day. Our results agree with taxi data obtained from nine major cities, and reveal that a remarkably small number of taxis can scan a large number of streets. This finding appears to be universal, indicating its applicability to cities beyond those analyzed here. Moreover, because taxi motions combine randomness and regularity (passengers' destinations being random, but the routes to them being deterministic), the spreading properties of taxi fleets are unusual; in stark contrast to random walks, the stationary densities of our taxi model obey Zipf's law, consistent with the empirical taxi data. Our results have direct utility for town councilors, smart-city designers, and other urban decision makers.

Quantifying the sensing power of crowd-sourced vehicle fleets
Kevin P. O'Keeffe, Amin Anjomshoaa, Steven H. Strogatz, Paolo Santi, Carlo Ratti

Source: (

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