Complex Systems Studies
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#complexity #complex_systems #networks #network_science

📨 Contact us: @carimi
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Don't miss the 3rd Edition of the Lake Como School on Complex Networks (http://ntmc.lakecomoschool.org/ ) & apply before the deadline.
🌀 You may have once seen a giant face in the clouds. Perhaps it took you aback, amused you, or maybe it prompted an “uncanny valley” kind of sensation—realness, but with a lingering unease.

🔗 http://nautil.us/blog/why-we-hear-voices-in-random-noise?utm_source=RSS_Feed&utm_medium=RSS&utm_campaign=RSS_Syndication

📌 Philip Jaekl is a freelance writer interested in cognitive neuroscience. He’s held postdoctoral research positions, investigating auditory-visual sensory integration, at Pompeu Fabra University in Barcelona and at the University of Rochester in New York State, where he currently resides.
🌀Non-equilibrium quantum systems
(Potentially useful lecture-note material)
Giuseppe E. Santoro,
SISSA, Trieste

🔗 http://indico.ictp.it/event/7644/material/2/2.pdf

Here is a collection of notes which contain material relevant to the Course on “Non-equilibrium quantum systems” held within the Spring College on “Physics of Complex Systems”. The material has no pretense of being coherently organized in any way. Being a “collage” of different lecture notes, please be aware that even the LaTex is not perfectly
consistent: there might be undefined references, or multiply defined labels. Sorry, this is not a book.
🗞 Who With Whom And How?: Extracting Large Social Networks Using Search Engines

Stefan Siersdorfer, Philipp Kemkes, Hanno Ackermann, Sergej Zerr

🔗 https://arxiv.org/pdf/1701.08285v1

📌ABSTRACT
Social network analysis is leveraged in a variety of applications such as identifying influential entities, detecting communities with special interests, and determining the flow of information and innovations. However, existing approaches for extracting social networks from unstructured Web content do not scale well and are only feasible for small graphs. In this paper, we introduce novel methodologies for query-based search engine mining, enabling efficient extraction of social networks from large amounts of Web data. To this end, we use patterns in phrase queries for retrieving entity connections, and employ a bootstrapping approach for iteratively expanding the pattern set. Our experimental evaluation in different domains demonstrates that our algorithms provide high quality results and allow for scalable and efficient construction of social graphs.
📄 Trade-offs between driving nodes and
time-to-control in complex networks

Sergio Pequito, Victor M. Preciado, #Barabasi , George J. Pappas

🔗 https://pdfs.semanticscholar.org/9217/cb81f364d6a5bad0f70d3c905ba49e6f4e5a.pdf

📌ABSTRACT
We first review some concepts from control theory , graph theory, and structural systems theory. We also include some notions of computational complexity needed in our analysis.
📄 Experimental econophysics: Complexity, selforganization, and emergent properties

J.P.Huang
Department of Physics and State Key Laboratory of Surface Physics, Fudan University, Shanghai 200433, China

🔗 http://polymer.bu.edu/hes/rp-huang15econ.pdf


📌 A B S T R A C T
Experimental econophysics is concerned with statistical physics of humans in the laboratory, and it is based on controlled human experiments developed by physicists to study some problems related toe conomics or finance. It relies on controlled human experiments in the laboratory together with agent-based modeling (for computer simulations and/or analytical theory), with an attempt to reveal the general cause-effect relationship between specific conditions and emergent properties of real economic/financial markets (a kind of complex adaptive systems). Here I #review the latest progress in the field, namely, stylized facts, herd behavior, contrarian behavior, spontaneous cooperation, partial information, and risk management. Also, I highlight the connections between such progress and other topics of traditional statistical physics. The main theme of the review is to show diverse emergent properties of the laboratory markets, originating from self-organization due to the nonlinear interactions among heterogeneous humans or agents (complexity).