***** To join INSNA, visit http://www.insna.org ***** Barry Wellman A vision is just a vision if it's only in your head Step by step, link by link, putting it together Streisand/Sondheim _______________________________________________________________________ NetLab Network FRSC INSNA Founder http://www.chass.utoronto.ca/~wellman twitter: @barrywellman NETWORKED: The New Social Operating System Lee Rainie & Barry Wellman http://amzn.to/zXZg39 _______________________________________________________________________ ---------- Forwarded message ---------- Date: Mon, 23 Jan 2017 12:02:55 +0000 From: "[utf-8] Complexity Digest" <[log in to unmask]> Reply-To: [log in to unmask] 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 http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=3801cff544&e=55e25a0e3e Dynamics on expanding spaces: modeling the emergence of novelties Novelties are part of our daily lives. We constantly adopt new technologies, conceive new ideas, meet new people, experiment with new situations. Occasionally, we as individuals, in a complicated cognitive and sometimes fortuitous process, come up with something that is not only new to us, but to our entire society so that what is a personal novelty can turn into an innovation at a global level. Innovations occur throughout social, biological and technological systems and, though we perceive them as a very natural ingredient of our human experience, little is known about the processes determining their emergence. Still the statistical occurrence of innovations shows striking regularities that represent a starting point to get a deeper insight in the whole phenomenology. This paper represents a small step in that direction, focusing on reviewing the scientific attempts to effectively model the emergence of the new and its regularities, with an emphasis on more recent contributions: from the plain Simon's model tracing back to the 1950s, to the newest model of Polya's urn with triggering of one novelty by another. What seems to be key in the successful modelling schemes proposed so far is the idea of looking at evolution as a path in a complex space, physical, conceptual, biological, technological, whose structure and topology get continuously reshaped and expanded by the occurrence of the new. Mathematically it is very interesting to look at the consequences of the interplay between the "actual" and the "possible" and this is the aim of this short review. Dynamics on expanding spaces: modeling the emergence of novelties Vittorio Loreto, Vito D. P. Servedio, Steven H. Strogatz, Francesca Tria Source: arxiv.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=3518e1783f&e=55e25a0e3e) Quantifying the diaspora of knowledge in the last century Academic research is driven by several factors causing different disciplines to act as ˙˙sources˙˙ or ˙˙sinks˙˙ of knowledge. However, how the flow of authors˙˙ research interests ˙˙ a proxy of human knowledge ˙˙ evolved across time is still poorly understood. Here, we build a comprehensive map of such flows across one century, revealing fundamental periods in the raise of interest in areas of human knowledge. We identify and quantify the most attractive topics over time, when a relatively significant number of researchers moved from their original area to another one, causing what we call a ˙˙diaspora of the knowledge˙˙ towards sinks of scientific interest, and we relate these points to crucial historical and political events. Noticeably, only a few areas ˙˙ like Medicine, Physics or Chemistry ˙˙ mainly act as sources of the diaspora, whereas areas like Material Science, Chemical Engineering, Neuroscience, Immunology and Microbiology or Environmental Science behave like sinks. Quantifying the diaspora of knowledge in the last century Manlio De Domenico, Elisa Omodei and Alex Arenas Applied Network Science20161:15 DOI: 10.1007/s41109-016-0017-9 Source: appliednetsci.springeropen.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=92af8ac8ed&e=55e25a0e3e) The global dynamical complexity of the human brain network How much information do large brain networks integrate as a whole over the sum of their parts? Can the dynamical complexity of such networks be globally quantified in an information-theoretic way and be meaningfully coupled to brain function? Recently, measures of dynamical complexity such as integrated information have been proposed. However, problems related to the normalization and Bell number of partitions associated to these measures make these approaches computationally infeasible for large-scale brain networks. Our goal in this work is to address this problem. Our formulation of network integrated information is based on the Kullback-Leibler divergence between the multivariate distribution on the set of network states versus the corresponding factorized distribution over its parts. We find that implementing the maximum information partition optimizes computations. These methods are well-suited for large networks with linear stochastic dynamics. We compute the integrated information for both, the system˙˙s attractor states, as well as non-stationary dynamical states of the network. We then apply this formalism to brain networks to compute the integrated information for the human brain˙˙s connectome. Compared to a randomly re-wired network, we find that the specific topology of the brain generates greater information complexity. The global dynamical complexity of the human brain network Xerxes D. Arsiwalla and Paul F. M. J. Verschure Source: appliednetsci.springeropen.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=6e0b047d81&e=55e25a0e3e) Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties There is a growing consensus that a fuller understanding of social cognition depends on more systematic studies of real-time social interaction. Such studies require methods that can deal with the complex dynamics taking place at multiple interdependent temporal and spatial scales, spanning sub-personal, personal, and dyadic levels of analysis. We demonstrate the value of adopting an extended multi-scale approach by re-analyzing movement time-series generated in a study of embodied dyadic interaction in a minimal virtual reality environment (a perceptual crossing experiment). Reduced movement variability revealed an interdependence between social awareness and social coordination that cannot be accounted for by either subjective or objective factors alone: it picks out interactions in which subjective and objective conditions are convergent (i.e., elevated coordination is perceived as clearly social, and impaired coordination is perceived as socially ambiguous). This finding is consistent with the claim that interpersonal interaction can be partially constitutive of direct social perception. Clustering statistics (Allan Factor) of salient events revealed fractal scaling. Complexity matching defined as the similarity between these scaling laws was significantly more pronounced in pairs of participants as compared to surrogate dyads. This further highlights the multi-scale and distributed character of social interaction and extends previous complexity matching results from dyadic conversation to non-verbal social interaction dynamics. Trials with successful joint interaction were also associated with an increase in local coordination. Consequently, a local coordination pattern emerges on the background of complex dyadic interactions in the PCE task and makes joint successful performance possible. Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties Leonardo Zapata-Fonseca, Dobromir Dotov, Ruben Fossion, and Tom Froese Front. Psychol., 12 December 2016 | http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c4b28aac39&e=55e25a0e3e Source: journal.frontiersin.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7add7fdd58&e=55e25a0e3e) A Novel Procedure for Measuring Semantic Synergy One interesting characteristic of some complex systems is the formation of macro level constructions perceived as having features that cannot be reduced to their micro level constituents. This characteristic is considered to be the expression of synergy where the joint action of the constituents produces unique features that are irreducible to the constituents isolated behavior or their simple composition. The synergy, characterizing complex systems, has been well acknowledged but difficult to conceptualize and quantify in the context of computing the emerging meaning of various linguistic and conceptual constructs. In this paper, we propose a novel measure/procedure for quantifying semantic synergy. This measure draws on a general idea of synergy as has been proposed in biology. We validate this measure by providing evidence for its ability to predict the semantic transparency of linguistic compounds (Experiment 1) and the abstractness rating of nouns (Experiment 2). A Novel Procedure for Measuring Semantic Synergy Yair Neuman, Yiftach Neuman, and Yochai Cohen Complexity Volume 2017 (2017), Article ID 5785617, 8 pages http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c6c93326bb&e=55e25a0e3e Source: www.hindawi.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=6de14f4be8&e=55e25a0e3e) ============================================== Sponsored by the Complex Systems Society. Founding Editor: Gottfried Mayer. Editor-in-Chief: Carlos Gershenson. 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