Complex Systems Studies

🍻 Networks at Nature https://www.nature.com/collections/adajhgjece/collection-team

Movienet: a movie multilayer network model using visual and textual semantic cues “multilayer network model to capture the narration of a movie based on its script, its subtitles, and the movie content” https://t.co/OBQzGfxdmy

Why Your Brain Needs Exercise https://www.scientificamerican.com/article/why-your-brain-needs-exercise/

Interesting new course by ⁦Aaron Clauset⁩ about Biological Networks (Fall 2019). Links and syllabus here: https://t.co/xGHs1o3S6S

#پیشنهاد 🧠 کنفرانس علوم اعصاب و فیزیک سامانه های نورونی 📌مهلت ارسال مقالات ۱ بهمن ماه 📌مهلت ثبت نام ۱۵ بهمن ماه 🔸 زمان برنامه: ۳۰ بهمن و ۱ اسفند 🔹 دانشگاه صنعتی شریف،دانشکده فیزیک اطلاعات بیشتر و ثبت نام: http://www.psi.ir/?neurophysics98 http://physics.sharif.ir/~web/neuroscience1398/

2020 Summer School in Social Neuroscience and Neuroeconomics Reminder that applications are due by January 1 for the 2020 Summer School in Social Neuroscience and Neuroeconomics (June 8-13) hosted at Duke: https://www.socialneuroecon.school/2020 There is no cost to attend the school; registration, lodging, and reasonable travel expenses will be covered for all attendees. The school is open to post-baccs, grad students, post-docs, and junior faculty. Priority will be given to individuals with research programs currently focused on improving health and well being in old age or who have plans to extend their work into this area (the school is funded by a grant from the National Institute on Aging). Individuals from backgrounds that are underrepresented in science are strongly encouraged to apply. If you are hesitant to apply because travel is complicated while you have an infant or small children, we will do everything we can to accommodate you. If there is interest, we will provide child care during the days and can provide space and time during the events for nursing and/or other childcare-related activities. If needed, we can express ship your pumped milk home to an infant using Milk Stork. If you missed the initial announcement, don’t worry - the application is one paragraph and we don’t request recommendation letters unless there is a multi-way tie for a spot. It should take about 20 minutes or less to apply, If you are local (Duke, UNC, etc) and won’t require lodging, you still need to complete an application to be able to attend. Hope to see you this summer at Duke! Gregory Samanez-Larkin http://mcablab.science/gregoryrsl ✔️ @ApplyTime

عنوان: دینامیک توازن در شبکه‌های درشت-دانه بندی شده 🗣 بهار بلوک آذری - دانشگاه شهید بهشتی ⏰ دوشنبه، ۹ دی ماه - ساعت ۱۵:۰۰ 🏛 محل برگزاری: سالن ابن‌هیثم ‍~~~~~~~~~~~~~~~~ 🕸 مرکز شبکه‌های پیچیده و علم داده اجتماعی دانشگاه شهید بهشتی تماس با ما: @ccnsd_admin 🕸 @CCNSD 🔗 ccnsd.ir —————————————

Recent developments on the performance of graphical LASSO networks http://psychosystems.org/glasso_developments ——————————————————————— A Tutorial on Regularized Partial Correlation Networks Sacha Epskamp, Eiko I. Fried https://arxiv.org/pdf/1607.01367 Recent years have seen an emergence of network modeling applied to moods, attitudes, and problems in the realm of psychology. In this framework, psychological variables are understood to directly affect each other rather than being caused by an unobserved latent entity. In this tutorial, we introduce the reader to estimating the most popular network model for psychological data: the partial correlation network. We describe how regularization techniques can be used to efficiently estimate a parsimonious and interpretable network structure in psychological data. We show how to perform these analyses in R and demonstrate the method in an empirical example on post-traumatic stress disorder data. In addition, we discuss the effect of the hyperparameter that needs to be manually set by the researcher, how to handle non-normal data, how to determine the required sample size for a network analysis, and provide a checklist with potential solutions for problems that can arise when estimating regularized partial correlation networks.

Statistical Machine Learning: Spring 2017 Instructors: Ryan Tibshirani (ryantibs at stat dot cmu dot edu) Larry Wasserman (larry at stat dot cmu dot edu) Notes, videos, cool plots: http://www.stat.cmu.edu/~ryantibs/statml/

Focus on #Multilayer #Networks edited for the New Journal of Physics @IOPscience. 23 outstanding papers were collected, check them at https://t.co/ndtwJgTVdu.

#سمینار_عمومی مدل ‌سازی و واکاوی فرآیندهای پخش در بسترهای اجتماعی - سه‌شنبه ۳ دی؛ ساعت ۱۶ الی ۱۷ - تالار ابن هیثم، دانشکده‌ فیزیک کانال انجمن علمی فیزیک بهشتی @sbu_physics

📺 https://youtu.be/HZGCoVF3YvM

🎅🏻 https://www.quantamagazine.org/quantas-year-in-math-and-computer-science-2019-20191223/

How connected is too connected? Impact of network topology on systemic risk and collapse of complex economic systems. arXiv:1912.09814v1 physics.soc-ph

#سمینارهای_هفتگی عنوان: Competitive Balance Theory: modeling the conflict of interest in a heterogeneous network 🗣 فریده علومی - دانشگاه شهید بهشتی ⏰ دوشنبه، ۲ دی - ساعت ۱۶:۰۰ 🏛 محل برگزاری: سالن ابن‌هیثم ‍~~~~~~~~~~~~~~~~ 🕸 مرکز شبکه‌های پیچیده و علم داده اجتماعی دانشگاه شهید بهشتی 🕸 @CCNSD 🔗 ccnsd.ir —————————————

🎤 سمینار عمومی این هفته دانشکده فیزیک 🗣 Ali Faqeeh, Postdoctoral Fellow, University of Limerick and Indiana University, Bloomington Title: Modelling and analysis of spreading processes in social platforms Abstract: The spreading processes appear on social systems in various forms, from the spread of diseases among civilians to information diffusion and dissemination of ideas, opinions or attitudes. The behavior of each of these phenomena is drawn from a rather complex set of characteristics of the agents (people) in the social system and also impacted by properties of the system such as the connection patterns between the individuals (i.e., the network structure) and the function and characteristics of the dynamics. In this seminar, I discuss our recent studies on social spreading processes, each of which concerns an interesting aspect of such phenomena. Firstly, I describe our recent analysis of the dissemination of scientific research using the body of the text of more than 230,000 publications. Then I talk about our analysis and modelling of information propagation on Twitter and show how similarity of users’ interests affects the diffusion of twits. Lastly, I introduce a new efficient metric for determining the most influential spreaders for various types of spreading processes that operate on social networks. 📆 سه‌شنبه، سوم دی‌ماه ⏰ ۴:۰۰ الی ۵:۰۰ بعدازظهر 🏛 تالار ابن‌هیثم، دانشکده فیزیک، دانشگاه شهید بهشتی

☑ Terry Tao reviews two new books about random matrix theory: https://t.co/HIk5jlQOX3

Fantastic collection of network science papers published in Nature journals https://t.co/Zljol7LfBj