💲 Fully funded PhD studentship in data science at Warwick business school

http://www.jobs.ac.uk/job/AWI911/phd-studentship-in-data-sciencemeasuring-and-predicting-human-behaviour-with-online-data/

🔸 http://www.nature.com/articles/s41562-016-0015

🗞 Why We Read Wikipedia

Philipp Singer, Florian Lemmerich, Robert West, Leila Zia, Ellery Wulczyn, Markus Strohmaier, Jure Leskovec

🔗 https://arxiv.org/pdf/1702.05379

📌 ABSTRACT
Wikipedia is one of the most popular sites on the Web, with millions of users relying on it to satisfy a broad range of information needs every day. Although it is crucial to understand what exactly these needs are in order to be able to meet them, little is currently known about why users visit Wikipedia. The goal of this paper is to fill this gap by combining a survey of Wikipedia readers with a log-based analysis of user activity. Based on an initial series of user surveys, we build a taxonomy of Wikipedia use cases along several dimensions, capturing users' motivations to visit Wikipedia, the depth of knowledge they are seeking, and their knowledge of the topic of interest prior to visiting Wikipedia. Then, we quantify the prevalence of these use cases via a large-scale user survey conducted on live Wikipedia with almost 30,000 responses. Our analyses highlight the variety of factors driving users to Wikipedia, such as current events, media coverage of a topic, personal curiosity, work or school assignments, or boredom. Finally, we match survey responses to the respondents' digital traces in Wikipedia's server logs, enabling the discovery of behavioral patterns associated with specific use cases. For instance, we observe long and fast-paced page sequences across topics for users who are bored or exploring randomly, whereas those using Wikipedia for work or school spend more time on individual articles focused on topics such as science. Our findings advance our understanding of reader motivations and behavior on Wikipedia and can have implications for developers aiming to improve Wikipedia's user experience, editors striving to cater to their readers' needs, third-party services (such as search engines) providing access to Wikipedia content, and researchers aiming to build tools such as recommendation engines.

🔹 http://www.nature.com/articles/s41559-017-0070

🔹 https://m.imgur.com/a/8M7q8#J7LANQ

http://www.biophysics.org/2017berlin/Home/tabid/7036/Default.aspx
Conformational Ensembles from Experimental Data and Computer Simulations
Berlin, Germany | Augst 25-29, 2017

⭕️ Dear All 

We have organized a talk by Daniel Bonn on "#Friction", Thursday, tomorrow, 23rd Feb 2017. Room 412, Physics Department, Sharif University of Technology. 

Due to short notice by Daniel this was done on a Thursday. 

Everyone is welcomed, and please advertise to those interested. 

Regards
Shahin Rouhani         
Sharif University of Technology and IPM 

​
🔹 14.00- 15.00 room 412 Thursday ​                                        

     Tel  : +98 21-66 16 45 06 
     Tel  : +98 21-66 00 54 10 
     Fax : +98 21-66 02 27 11

🎞 https://www.instagram.com/p/BQ0iSvNA6j5/

🎞 https://simons.berkeley.edu/talks/john-baez-12-06-2016

The first ever Network #Neuroscience Satellite! Apply soon:
🔗 http://www.complexity.es/netsci2017brain

🔹 The Amazing, Autotuning Sandpile

A simple mathematical model of a sandpile shows remarkably complex behavior.

BY JORDAN ELLENBERG
🔗 http://nautil.us/issue/23/Dominoes/the-amazing-autotuning-sandpile

💲 http://pnas.org/content/113/36/10031.abstract

DebtRank as a fine example of the importance of networks & complexity in finance!

🖥 A visualization of the Hopf fibration
http://nilesjohnson.net/hopf.html?platform=hootsuite

Hopf fibration -- fibers and base

🗞 Network neuroscience

Danielle S Bassett & Olaf Sporns

🔗 http://www.nature.com/neuro/journal/v20/n3/full/nn.4502.html

📌 ABSTRACT
Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, #brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We #review emerging trends in #network #neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.

#سمینارهای_هفتگی گروه سیستم‌های پیچیده و علم شبکه دانشگاه شهید بهشتی

🔹دوشنبه، ۹ اسفندماه، ساعت ۴/۵ - کلاس ۴ دانشکده فیزیک دانشگاه شهید بهشتی

@carimi

“Phase Transition in Dynamic Networks”
- Fereshteh Rabbani, Physics Ph.D. candidate at SBU

Abstract
There is a long-standing belief that in signed networks with simultaneous friendly/hostile interactions there is a general tendency to a global balance. Although Balance represents a state of the network with a lack of contentious situations, real networks have always tensions. Contrary to the impression, networks transition from unbalanced and tension state to a steady state is not smooth, it’s involved abrupt change.
Since the emergence of balance occurs in zero temperature, in this work, we implemented simple dynamical rules for updating links in imbalanced triads and present an analytic mean-field solution which is exact in the limit of large network size. Previous simulations of balanced dynamics have a long history that dates back to the Antal model. Here, we present a new link-based model for the evolution of network as a function of temperature. With this dynamics, a fully connected network undergoes a first order phase transition from an unbalanced state to stability. Our solution shows that; a network falls into balanced or unbalanced absorbing state according to the initial state.

🔹Feel free to contact us: @carimi

سه‌شنبه، ۱۰ اسفندماه
ساعت ۳ الی ۴ بعداز ظهر
سالن ابن‌هیثم، دانشکده فیزیک٬ دانشگاه شهید بهشتی

🔹 http://www.uvm.edu/pdodds/teaching/courses/pocs/