Collection |

Complexity Research in Nature Communications

This web collection showcases the potential of interdisciplinary complexity research by bringing together a selection of recent Nature Communications articles investigating complex systems. Complexity research aims to characterize and understand the behaviour and nature of systems made up of many interacting elements. Such efforts often require interdisciplinary collaboration and expertise from diverse schools of thought. Nature Communications publishes papers across a broad range of topics that span the physical and life sciences, making the journal an ideal home for interdisciplinary studies.

The Ecology and evolution section contains studies that explore the dynamics of networks of genes, individuals and communities using combinations of empirical data and mathematical tools. Other examples of computational modeling in biology include studies on precision medicine and molecular network dynamics, and these are highlighted in Network medicine tab. Neuroscience is another discipline that is effectively leveraging network analysis to better understand how the complex interactions between neuroanatomy and function give rise to equally complex human behaviors. Such behaviors, when combined, give rise to cultures and societies.  The latter are paradigmatic complex systems, and articles presented in the Social systems section examine these paradigmatic complex systems, describing the dynamics of social systems, financial systems and transport networks that affect much of our daily lives.  Finally, the collection under the Network structure and dynamics tab showcases methodological advances in complex system modeling and network analysis. The articles that we felt represented each section particularly well are also available in the Editors' picks section, below.  

Solving some of the most important problems in science may only be possible when scientists with different backgrounds collaborate to address shared questions using complementary techniques. Truly interdisciplinary research that can bridge the natural, physical and social sciences remains challenging, as it requires scientists to share and discuss their views across disciplines, and therefore such research must also be able to reach a diverse audience. Our collection, which has been chosen by editors across the broad spectrum of subjects covered by Nature Communications, has been put together with this specific goal in mind.  


Social systems

Optimal diversification strategies in the networks of related products and of related research areas
Aamena Alshamsi et al.Nat. Commun. 9 1328 (2018)

The probability that a region will develop a particular research activity increases with the number of similar activities in neighbouring regions. Here the authors analyse diffusion strategies and show that it is not only important to know which activities to target but also when to target them.


Morphology of travel routes and the organization of cities
Minjin Lee et al.Nat. Commun. 8 2229 (2017)

The street networks of cities may be viewed as complex networks with evolving structure. Here, the authors investigate the shape of travel routes in 92 cities and define a metric called inness, they show which reveals connections between common urban features in cities with similar inness profiles, correlating with their stage of urban development as measured by a series of socio-economic and infrastructural indicators.


Universal model of individual and population mobility on diverse spatial scales
Xiao-Yong Yan et al.Nat. Commun. 8 1639 (2017)

Understanding and accurate prediction of human mobility is of increasing importance, but a universal framework is lacking. Here, the authors develop a unified model, which, by combining memory effect and population-induced competition, enables accurate prediction of both individual and population mobility on diverse spatial scales based on population distribution only.


Diffusion of treatment in social networks and mass drug administration
Goylette F. Chami et al.Nat. Commun. 8 1929 (2017)

The success of mass drug administration depends on the distributors’ contact and engagement with members of their communities. Using data of deworming treatment distribution from Ugandan villages, the authors here demonstrate that community medicine distributors with tightly-knit friendship connections achieve the greatest reach and speed of coverage, suggesting that clustering should be considered when planning large-scale treatment campaigns. 


Control of finite critical behaviour in a small-scale social system
Bryan C. Daniels et al.Nat. Commun. 8 14301 (2017)

Proximity of social systems to criticality can facilitate large-scale social changes and might be advantageous under changing conditions, but it also entails reduced robustness. Here, the authors analyse fight size distributions in a macaque society and find not only that it sits near criticality, but also that the distance from the critical point is tuneable through adjustment of individual behaviour and social conflict management.

Exercise contagion in a global social network
Sinan Aral and Christos Nicolaides, Nat. Commun. 8 14753 (2017)

Some argue that health-related behaviours, such as obesity, are contagious, but empirical evidence of health contagion remains inconclusive. Here, using a large scale quasi-experiment in a global network of runners, Aral and Nicolaides show that this type of contagion exists in fitness behaviours, and that this contagiousness varies with the relative activity and gender relationships between friends. These results can be explained by the Embeddedness and Structural Diversity theories of social contagion, but not by the Complex Contagion theory.

Pathways towards instability in financial networks
Marco Bardoscia et al.Nat. Commun. 8 14416 (2017)

Similarly to complex ecosystems, propagation of distress through the network of financial systems is influenced by its topological features. Models for financial risks are however often based on specific kinds of interactions, rather than looking if topology creates instability. Here the authors show, independently of specific financial models, that processes that are widely believed to stabilize the financial system can actually drive it towards instability by creating cyclical structures that amplify distress.

Inferring personal economic status from social network location
Shaojun Luo et al., Nat. Commun. 8 15227 (2017)

Anecdotal and qualitative evidence suggests that the economic status of an individual is reflected in the structure of their social ties. Here the authors provide a quantitative interpretation to this idea, showing that an individual’s collective influence to the structural integrity of the global social network can be used to infer their economic wellness. For validating this conclusion, the authors carried out a marketing campaign targeted on the basis of this idea, reporting a three-fold increase in response rate in comparison to random targeting.

Returners and explorers dichotomy in human mobility
Luca Pappalardo et al., Nat. Commun. 6, 8166 (2015)

Previous studies of human transport data established that individuals' travelling behaviour exhibits both a great variability in the travelled distance and a high predictability of their future locations. Here the authors analyse GPS and mobile phone data to systematically investigate the impact of recurrent mobility on the travelled distance. Two classes of mobility patterns are identified and modelled: returners and explorers, with the latter playing a quantifiable role in spreading phenomena.

Understanding congested travel in urban areas
Serdar Çolak et al., Nat. Commun. 7 10793 (2016)

Rapid urbanization and increasing demand for transportation have burdened the urban road infrastructure. And since modifications to the actual road capacity are often impractical, it is interesting to explore the possibility of alleviating congestion by modifying route choices. Here, the authors demonstrate on the basis of mobile phone traces during morning peak hours that a ratio of the road supply to the travel demand explains the time lost in congestion, and evaluate the effect of a congestion relief approach under a centralized routing scheme.

Social learning strategies modify the effect of network structure on group performance
Daniel Barkoczi and Mirta Galesic, Nat. Commun. 7 13109 (2016)

Communication networks may be efficient (well connected) or inefficient (poorly connected). Previous studies have disagreed over whether efficient or inefficient network structures should be more effective in promoting group performance. Here, Barkoczi and Galesic demonstrate that which structure is superior depends on the social learning strategy used by individuals in the network. Efficient networks produce higher group performance when individuals copy solutions that are popular amongst their contacts, but not when individuals copy the most successful group member.

Topological data analysis of contagion maps for examining spreading processes on networks
Dane Taylor et al., Nat. Commun. 6 7723 (2015)

Social and biological contagions are influenced by the spatial features of the underlying network. In modern contagions, the existence of long-range edges - such as airline transportation - must be also taken into account. Here, Taylor et al. introduce an approach based on the analysis of topological data athat incorporates these long-range connections and that can be used to help modelling, forecasting and controlling the spreading processes involved in such contagions.