Simplifying Complexity
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Simplifying Complexity
ecology and complexity science
Curated by Eric L Berlow
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The Scaling of Human Interactions with City Size

The pace of life accelerates with city size, manifested in a per capita increase of almost all socioeconomic rates such as GDP, wages, violent crime or the transmission of certain contagious diseases. Here, we show that the structure and dynamics of the underlying network of human interactions provides a possible unifying mechanism for the origin of these pervasive regularities. By analyzing billions of anonymized call records from two European countries we find that human social interactions follow a superlinear scale-invariant relationship with city population size. This systematic acceleration of the interaction intensity takes place within specific constraints of social grouping. Together, these results provide a general microscopic basis for a deeper understanding of cities as co-located social networks in space and time, and of the emergent urban socioeconomic processes that characterize complex human societies.

 

The Scaling of Human Interactions with City Size

Markus Schläpfer, Luis M. A. Bettencourt, Mathias Raschke, Rob Claxton, Zbigniew Smoreda, Geoffrey B. West, Carlo Ratti

http://arxiv.org/abs/1210.5215


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When Networks Network

When Networks Network | Simplifying Complexity | Scoop.it

When networks depend on other networks, such as a communications network that relies on a power grid, failure can cascade back and forth between the two. This behavior may explain sudden breakdowns in interacting systems. Thus, the effects of an attack on a single node can reduce an übernetwork  that starts with 12 operating nodes to just four.

Once studied solo, systems display surprising behavior when they interact.

 


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Diverse stock portfolios break down under market stress

Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongoing financial crisis. However, in complex systems, such as financial systems, correlations are not constant but instead vary in time. Here we address the question of quantifying state-dependent correlations in stock markets. Reliable estimates of correlations are absolutely necessary to protect a portfolio. We analyze 72 years of daily closing prices of the 30 stocks forming the Dow Jones Industrial Average (DJIA). We find the striking result that the average correlation among these stocks scales linearly with market stress reflected by normalized DJIA index returns on various time scales. Consequently, the diversification effect which should protect a portfolio melts away in times of market losses, just when it would most urgently be needed. Our empirical analysis is consistent with the interesting possibility that one could anticipate diversification breakdowns, guiding the design of protected portfolios.

 

Quantifying the Behavior of Stock Correlations Under Market Stress

Tobias Preis, Dror Y. Kenett, H. Eugene Stanley, Dirk Helbing & Eshel Ben-Jacob

Scientific Reports 2, Article number: 752 http://dx.doi.org/10.1038/srep00752


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Mesoscale symmetries explain dynamical equivalence of food webs

A goal of complex system research is to identify the dynamical implications of network structure. While early results focused mainly on local or global structural properties, there is now growing interest in mesoscale structures that comprise more than one node but not the whole network. A central challenge is to discover under what conditions the occurrence of a specific mesoscale motif already allows conclusions on the dynamics of a network as a whole. In this paper, we investigate the dynamics of ecological food webs, complex heterogeneous networks of interacting populations.

 

Mesoscale symmetries explain dynamical equivalence of food webs

Helge Aufderheide, Lars Rudolf and Thilo Gross

New J. Phys. 14 105014

http://dx.doi.org/10.1088/1367-2630/14/10/105014


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Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread

The dynamics of infectious diseases caused by pathogens transmissible from human to human strongly depends on contact patterns between individuals. High quality observational data on contact patterns, usually presented in the form of age-specific contact matrices, are difficult to gather and are currently available only for few countries worldwide. Here we propose a computational approach, based on the simulation of a virtual society of agents, allowing the estimation of contact patterns by age for 26 European countries.

 

Fumanelli L, Ajelli M, Manfredi P, Vespignani A, Merler S (2012) Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread. PLoS Comput Biol 8(9): e1002673. http://dx.doi.org/10.1371/journal.pcbi.1002673


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Ten Simple Rules for Online Learning

The success of online courseware such as that offered by the Massachusetts Institute of Technology (MIT) (http://ocw.mit.edu) and now by many other institutions, together with a plethora of recent announcements of major new initiatives in this arena such as Coursera (https://www.coursera.org), Udacity (http://www.udacity.com), and the Harvard-MIT partnership edX (http://www.edxonline.org), have made it clear that online learning has reached a tipping point. Many signs point to the possibility in the near future of getting a quality, university-level education at a distance, and for free. As exciting as this prospect may be, it behooves online students to follow a few simple rules for getting the most out of the experience, while being realistic in their expectations, as outlined below.

 

Searls DB (2012) Ten Simple Rules for Online Learning. PLoS Comput Biol 8(9): e1002631. http://dx.doi.org/10.1371/journal.pcbi.1002631


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A 61-million-person experiment in social influence and political mobilization - strong social ties matter

A 61-million-person experiment in social influence and political mobilization - strong social ties matter | Simplifying Complexity | Scoop.it

Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies, and it is unknown whether online social networks operate in the same way. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users’ friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between ‘close friends’ who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks.

 

A 61-million-person experiment in social influence and political mobilization

Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle & James H. Fowler

Nature 489, 295–298 (13 September 2012) http://dx.doi.org/10.1038/nature11421


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BBC Documentary Climate Wars Episode 2

A great homework video for the IB Biology Ecology Topic (links to ToK).
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Quantifying the Behavior of Stock Correlations Under Market Stress

Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongoing financial crisis. However, in complex systems, such as financial systems, correlations are not constant but instead vary in time. Here we address the question of quantifying state-dependent correlations in stock markets. Reliable estimates of correlations are absolutely necessary to protect a portfolio. We analyze 72 years of daily closing prices of the 30 stocks forming the Dow Jones Industrial Average (DJIA). We find the striking result that the average correlation among these stocks scales linearly with market stress reflected by normalized DJIA index returns on various time scales. Consequently, the diversification effect which should protect a portfolio melts away in times of market losses, just when it would most urgently be needed. Our empirical analysis is consistent with the interesting possibility that one could anticipate diversification breakdowns, guiding the design of protected portfolios.

 

Quantifying the Behavior of Stock Correlations Under Market Stress

Tobias Preis, Dror Y. Kenett, H. Eugene Stanley, Dirk Helbing & Eshel Ben-Jacob

Scientific Reports 2, Article number: 752 http://dx.doi.org/10.1038/srep00752


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Anticipating Critical Transitions or Tipping Points in complex systems

Tipping points in complex systems may imply risks of unwanted collapse, but also opportunities for positive change. Our capacity to navigate such risks and opportunities can be boosted by combining emerging insights from two unconnected fields of research. One line of work is revealing fundamental architectural features that may cause ecological networks, financial markets, and other complex systems to have tipping points. Another field of research is uncovering generic empirical indicators of the proximity to such critical thresholds. Although sudden shifts in complex systems will inevitably continue to surprise us, work at the crossroads of these emerging fields offers new approaches for anticipating critical transitions.

 

Anticipating Critical Transitions
Marten Scheffer et al.

Science 19 October 2012:
Vol. 338 no. 6105 pp. 344-348
http://dx.doi.org/10.1126/science.1225244


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Anticipating Critical Transitions in complex systems

Tipping points in complex systems may imply risks of unwanted collapse, but also opportunities for positive change. Our capacity to navigate such risks and opportunities can be boosted by combining emerging insights from two unconnected fields of research. One line of work is revealing fundamental architectural features that may cause ecological networks, financial markets, and other complex systems to have tipping points. Another field of research is uncovering generic empirical indicators of the proximity to such critical thresholds. Although sudden shifts in complex systems will inevitably continue to surprise us, work at the crossroads of these emerging fields offers new approaches for anticipating critical transitions.

 

Anticipating Critical Transitions
Marten Scheffer et al.

Science 19 October 2012:
Vol. 338 no. 6105 pp. 344-348
http://dx.doi.org/10.1126/science.1225244


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Control Centrality and Hierarchical Structure in Complex Networks

Control Centrality and Hierarchical Structure in Complex Networks | Simplifying Complexity | Scoop.it

We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks.


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Future impact: Predicting scientific success

To construct a formula to predict future h-index, we assembled a large data set and analysed it using machine-learning techniques. Our initial sample from academictree.org — a crowd-sourced website listing scientists' mentors, trainees and collaborators — contains the names and institutions of about 34,800 neuroscientists, 2,000 scientists studying the fruitfly Drosophila and 1,300 evolutionary researchers. We matched these authors to records in Scopus, an online database of academic papers and citation data. We restricted our analysis to authors who had accrued an h-index greater than 4 (to exclude inactive scientists); to publications after 1995 (because electronic records are sparse before then); to authors who had published their first manuscript in the past 5–12 years; and to authors who were identifiable in Scopus.

 

Future impact: Predicting scientific success

Daniel E. Acuna, Stefano Allesina & Konrad P. Kording

Nature 489, 201–202 (13 September 2012) http://dx.doi.org/10.1038/489201a


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Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread

The dynamics of infectious diseases caused by pathogens transmissible from human to human strongly depends on contact patterns between individuals. High quality observational data on contact patterns, usually presented in the form of age-specific contact matrices, are difficult to gather and are currently available only for few countries worldwide. Here we propose a computational approach, based on the simulation of a virtual society of agents, allowing the estimation of contact patterns by age for 26 European countries.

 

Fumanelli L, Ajelli M, Manfredi P, Vespignani A, Merler S (2012) Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread. PLoS Comput Biol 8(9): e1002673. http://dx.doi.org/10.1371/journal.pcbi.1002673


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Earth's Last Unexplored Wilderness: Your Very Own Home

Earth's Last Unexplored Wilderness: Your Very Own Home | Simplifying Complexity | Scoop.it

Biologists are starting to explore the woolly ecosystems in our homes and hospitals, and figuring out how they can make us sick or keep us healthy.


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