Statistical relationships among the variables of a complex system reveal a lot about its physical behavior. Therefore, identification of the relevant variables and characterization of their interactions are crucial for a better understanding of a complex system. Correlation-based techniques have been widely utilized to elucidate the linear statistical dependencies in many science and engineering applications. However, for the analysis of nonlinear dependencies, information-theoretic quantities, such as Mutual Information (MI) and the Transfer Entropy (TE), have been proven to be superior. MI quantifies the amount of information obtained about one random variable, through the other random variable, and it is symmetric. As an asymmetrical measure, TE quantifies the amount of directed (time-asymmetric) transfer of information between random processes and therefore is related to the measures of causality.

https://doi.org/10.3390/books978-3-03842-920-3 Open Access
© 2018 MDPI; under CC BY-NC-ND license
Transfer Entropy
Deniz Gençağa (Ed.)
Pages: VIII, 326
Published: August 2018

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This book introduces a new approach to environmental sociology, by integrating complexity-informed social science, Marxian ecological theory, and resilience-based human ecology. It argues that sociologists have largely ignored developments in ecology which move beyond functionalist approaches to systems analysis, and as a result, environmental sociology has failed to capitalise not only on the analytical promise of resilience ecology, but on complementary developments in complexity theory. By tracing the origins and discussing current developments in each of these areas, it offers several paths to interdisciplinary dialogue. Eoin Flaherty argues that complexity theory and Marxian ecology can enhance our understanding of the social aspect of social-ecological systems, whilst a resilience approach can sharpen the analytical power of environmental sociology.

Complexity and Resilience in the Social and Ecological Sciences
Eoin Flaherty

Springer

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This text is about spreading of information and influence in complex networks. Although previously considered similar and modeled in parallel approaches, there is now experimental evidence that epidemic and social spreading work in subtly different ways. While previously explored through modeling, there is currently an explosion of work on revealing the mechanisms underlying complex contagion based on big data and data-driven approaches.

This volume consists of four parts. Part 1 is an Introduction, providing an accessible summary of the state-of-the-art. Part 2 provides an overview of the central theoretical developments in the field. Part 3 describes the empirical work on observing spreading processes in real-world networks. Finally, Part 4 goes into detail with recent and exciting new developments: dedicated studies designed to measure specific aspects of the spreading processes, often using randomized control trials to isolate the network effect from confounders, such as homophily.

Each contribution is authored by leading experts in the field. This volume, though based on technical selections of the most important results on complex spreading, remains quite accessible to the newly interested. The main benefit to the reader is that the topics are carefully structured to take the novice to the level of expert on the topic of social spreading processes. This book will be of great importance to a wide field: from researchers in physics, computer science, and sociology to professionals in public policy and public health.

Complex Spreading Phenomena in Social Systems
Influence and Contagion in Real-World Social Networks
Editors: Sune Lehmann, Yong-Yeol Ahn

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This thesis looks at how cities operate as Complex Adaptive Systems (CAS). It focuses on how certain characteristics of urban form can support an urban environment’s capacity to self-organize, enabling emergent features to appear that, while unplanned, remain highly functional. The research is predicated on the notion that CAS processes operate across diverse domains: that they are ‘generalized’ or ‘universal’. The goal of the dissertation is then to determine how such generalized principles might ‘play out’ within the urban fabric. The main thrust of the work is to unpack how elements of the urban fabric might be considered as elements of a complex system and then identify how one might design these elements in a more deliberate manner, such that they hold a greater embedded capacity to respond to changing urban forces. The research is further predicated on the notion that, while such responses are both imbricated with, and stewarded by human actors, the specificities of the material characteristics themselves matter. Some forms of material environments hold greater intrinsic physical capacities (or affordances) to enact the kinds of dynamic processes observed in complex systems than others (and can, therefore, be designed with these affordances in mind). The primary research question is thus:

What physical and morphological conditions need to be in place within an urban environment in order for Complex Adaptive Systems dynamics arise – such that the physical components (or ‘building blocks’) of the urban environment have an enhanced capacity to discover functional configurations in space and time as a response to unfolding contextual conditions?

WOHL, Sharon. Complex Adaptive Systems & Urban Morphogenesis. A+BE | Architecture and the Built Environment, [S.l.], n. 10, p. 1-238, june 2018. ISSN 2214-7233. Available at: <https://journals.open.tudelft.nl/index.php/abe/article/view/2397>. Date accessed: 12 june 2018. doi: https://doi.org/10.7480/abe.2018.10.

Source: journals.open.tudelft.nl

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