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Learn about the latest and greatest related to complex systems research. More at

Large-scale physical activity data reveal worldwide activity inequality

    To be able to curb the global pandemic of physical inactivity and the 
associated 5.3 million deaths per year, we need to understand the basic 
principles that govern physical activity. However, there is a lack of 
large-scale measurements of physical activity patterns across free-living 
populations worldwide. Here we leverage the wide usage of smartphones with 
built-in accelerometry to measure physical activity at the global scale. 
We study a dataset consisting of 68 million days of physical activity for 
717,527 people, giving us a window into activity in 111 countries across 
the globe. We find inequality in how activity is distributed within 
countries and that this inequality is a better predictor of obesity 
prevalence in the population than average activity volume. Reduced 
activity in females contributes to a large portion of the observed 
activity inequality. Aspects of the built environment, such as the 
walkability of a city, are associated with a smaller gender gap in 
activity and lower activity inequality. In more walkable cities, activity 
is greater throughout the day and throughout the week, across age, gender, 
and body mass index (BMI) groups, with the greatest increases in activity 
found for females. Our findings have implications for global public health 
policy and urban planning and highlight the role of activity inequality 
and the built environment in improving physical activity and health

Large-scale physical activity data reveal worldwide activity inequality
Tim Althoff, Rok Sosi˙˙, Jennifer L. Hicks, Abby C. King, Scott L. Delp & Jure Leskovec
Nature 547, 336˙˙339 (20 July 2017) doi:10.1038/nature23018

Source: (

Why teach modeling & simulation in schools?

    Advancements in science and technology take place on a global scale without much consideration of the exact implications that they may essentially have on the species or our planet. Over the last few decades, things are moving very fast and not always in a good way. The climate of the planet is changing drastically. Ice caps are melting faster than ever. Known animal species around the world are declining at rates faster than ever previously known in recorded history. We humans, might have intelligent individuals amidst us. However, collectively, to any external observer, we would perhaps seem to act more like mindless scavengers stripping the planet of its resources faster than she can ever replenish them. And this all seems to be intrinsically linked with our seemingly insatiable ˙˙collective˙˙ urge to satisfy immediate needs. So, while the technological revolution has greatly benefited humankind, our continual reliance on technology also has considerable collateral effects
on the planet.

Why teach modeling & simulation in schools?
Muaz A. Niazi and Anatoly Temkin
Complex Adaptive Systems Modeling20175:7

Source: (

CompleNet 2018 ˙˙ 9th Conference on Complex Networks

CompleNet is an international conference that brings together researchers and practitioners from diverse disciplines˙˙from sociology, biology, physics, and computer science˙˙who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.

CompleNet 2018 - 9th Conference on Complex Networks

Boston (MA, US)

March 5-8, 2018

Source: (

The angular nature of road networks

    Road networks are characterised by several structural and geometrical 
properties. The topological structure determines partially the 
hierarchical arrangement of roads, but since these are networks that are 
spatially constrained, geometrical properties play a fundamental role in 
determining the network˙˙s behaviour, characterising the influence of each 
of the street segments on the system. In this work, we apply percolation 
theory to the UK˙˙s road network using the relative angle between street 
segments as the occupation probability. The appearance of the spanning 
cluster is marked by a phase transition, indicating that the system 
behaves in a critical way. Computing Shannon˙˙s entropy of the cluster 
sizes, different stages of the percolation process can be discerned, and 
these indicate that roads integrate to the giant cluster in a hierarchical 
manner. This is used to construct a hierarchical index that serves to 
classify roads in terms of their importance. The obtained classification 
is in very good correspondence with the official designations of roads. 
This methodology hence provides a framework to consistently extract the 
main skeleton of an urban system and to further classify each road in 
terms of its hierarchical importance within the system.

The angular nature of road networks
Carlos Molinero, Roberto Murcio & Elsa Arcaute
Scientific Reports 7, Article number: 4312 (2017)

Source: (

Improving the Economic Complexity Index

    How much knowledge is there in an economy? In recent years, data on the mix of products that countries export has been used to construct measures of economic complexity that estimate the knowledge available in an economy and predict future economic growth. Here we introduce a new and simpler metric of economic complexity (ECI+) that measures the total exports of an economy corrected by how difficult it is to export each product. We use data from 1973 to 2013 to compare the ability of ECI+, the Economic Complexity Index (ECI), and Fitness complexity, to predict future economic growth using 5, 10, and 20-year panels in a pooled OLS, a random effects model, and a fixed effects model. We find that ECI+ outperforms ECI and Fitness in its ability to predict economic growth and in the consistency of its estimators across most econometric specifications. On average, one standard deviation increase in ECI+ is associated with an increase in annualized growth of about 4% to 5%. We then
combine ECI+ with measures of physical capital, human capital, and institutions, to find a robust model of economic growth. The ability of ECI+ to predict growth, and the value of its coefficient, is robust to these controls. Also, we find that human capital, political stability, and control of corruption; are positively associated with future economic growth, and that income is negatively associated with growth, in agreement with the traditional growth literature. Finally, we use ECI+ to generate economic growth predictions for the next 20 years and compare these predictions with the ones obtained using ECI and Fitness. These findings improve the methods available to estimate the knowledge intensity of economies and predict future economic growth.

Improving the Economic Complexity Index
Saleh Albeaik, Mary Kaltenberg, Mansour Alsaleh, Cesar A. Hidalgo

Source: (

Video Pandemics: Worldwide Viral Spreading of Psy˙˙s Gangnam Style Video

    Viral videos can reach global penetration traveling through international channels of communication similarly to real diseases starting from a well-localized source. In past centuries, disease fronts propagated in a concentric spatial fashion from the the source of the outbreak via the short range human contact network. The emergence of long-distance air-travel changed these ancient patterns. However, recently, Brockmann and Helbing have shown that concentric propagation waves can be reinstated if propagation time and distance is measured in the flight-time and travel volume weighted underlying air-travel network. Here, we adopt this method for the analysis of viral meme propagation in Twitter messages, and define a similar weighted network distance in the communication network connecting countries and states of the World. We recover a wave-like behavior on average and assess the randomizing effect of non-locality of spreading. We show that similar result can be recovered
from Google Trends data as well.

Video Pandemics: Worldwide Viral Spreading of Psy's Gangnam Style Video
Zsofia Kallus, Daniel Kondor, Jozsef Steger, Istvan Csabai, Eszter Bokanyi, Gabor Vattay

Source: (

The spread of fake news by social bots

The massive spread of fake news has been identified as a major global risk 
and has been alleged to influence elections and threaten democracies. 
Communication, cognitive, social, and computer scientists are engaged in 
efforts to study the complex causes for the viral diffusion of digital 
misinformation and to develop solutions, while search and social media 
platforms are beginning to deploy countermeasures. However, to date, these 
efforts have been mainly informed by anecdotal evidence rather than 
systematic data. Here we analyze 14 million messages spreading 400 
thousand claims on Twitter during and following the 2016 U.S. presidential 
campaign and election. We find evidence that social bots play a key role 
in the spread of fake news. Accounts that actively spread misinformation 
are significantly more likely to be bots. Automated accounts are 
particularly active in the early spreading phases of viral claims, and 
tend to target influential users. Humans are vulnerable to this 
manipulation, retweeting bots who post false news. Successful sources of 
false and biased claims are heavily supported by social bots. These 
results suggests that curbing social bots may be an effective strategy for 
mitigating the spread of online misinformation.

The spread of fake news by social bots

Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Alessandro Flammini, Filippo Menczer

Source: (

The Ninth International Conference on Guided Self-Organisation (GSO-2018) : Information Geometry and Statistical Physics

    March 26 - 28, 2018
Max Planck Institute for Mathematics in the Sciences

The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization (i.e., its simplicity, parallelization, adaptability, robustness, scalability) while still being able to direct the outcome of the self-organizing process. GSO typically has the following features:

(i) An increase in organization (i.e., structure and/or functionality) over time;

(ii) Local interactions that are not explicitly guided by any external agent;

(iii) Task-independent objectives that are combined with task-dependent constraints.

GSO-2018 is the 9th conference in a bi-annual series on GSO. Recent research is starting to indicate that information geometry, nonequilibrium statistical physics in general, and the thermodynamics of computation in particular, all play a key role in GSO. Accordingly, a particular focus of this conference will be the interplay of those three topics as revealed by their relationship with GSO.

Source: (

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Editor-in-Chief: Carlos Gershenson.

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