Do you want to study complex systems? https://t.co/zTYHTUC1o1.
admissions open until 3.1.2020! #MSc #complexity https://t.co/cbCqjU6aaR
admissions open until 3.1.2020! #MSc #complexity https://t.co/cbCqjU6aaR
Forwarded from Complex Networks (SBU)
🎤 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
🗣 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
Forwarded from Complex Networks (SBU)
#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
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🕸 مرکز شبکههای پیچیده و علم داده اجتماعی دانشگاه شهید بهشتی
🕸 @CCNSD 🔗 ccnsd.ir
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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
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How connected is too connected? Impact of network topology on systemic risk and collapse of complex economic systems.
arXiv:1912.09814v1 physics.soc-ph
arXiv:1912.09814v1 physics.soc-ph
Forwarded from انجمن علمی فیزیک بهشتی (SBU)
#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
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
Focus on #Multilayer #Networks edited for the New Journal of Physics @IOPscience. 23 outstanding papers were collected, check them at https://t.co/ndtwJgTVdu.
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/
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/
Recent developments on the performance of graphical LASSO networks
http://psychosystems.org/glasso_developments
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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.
http://psychosystems.org/glasso_developments
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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.
psychosystems
Recent developments on the performance of graphical LASSO networks
This post was written by Sacha Epskamp, Gaby Lunansky, PIa Tio and Denny Borsboom, on behalf of the Psychosystems lab group. Currently, many network models are estimated using LASSO regularization. For ordinal and continuous variables, a
Forwarded from Complex Networks (SBU)
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
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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
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