🔖 How to Maximize the Spread of Social Influence: A Survey

Giuseppe De Nittis, Nicola Gatti

🔗 https://arxiv.org/pdf/1806.07757.pdf

📌 ABSTRACT
This survey presents the main results achieved for the influence maximization problem in social networks. This problem is well studied in the literature and, thanks to its recent applications, some of which currently deployed on the field, it is receiving more and more attention in the scientific community. The problem can be formulated as follows: given a graph, with each node having a certain probability of influencing its neighbors, select a subset of vertices so that the number of nodes in the network that are influenced is maximized. Starting from this model, we introduce the main theoretical developments and computational results that have been achieved, taking into account different diffusion models describing how the information spreads throughout the network, various ways in which the sources of information could be placed, and how to tackle the problem in the presence of uncertainties affecting the network. Finally, we present one of the main application that has been developed and deployed exploiting tools and techniques previously discussed.

✔ https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.062136

https://www.crcpress.com/Nonlinear-Dynamics-and-Chaos-With-Applications-to-Physics-Biology-Chemistry/Strogatz/p/book/9780813349107?utm_source=twitter&utm_medium=post&utm_campaign=180616477https://www.

🎞 Topology matters:
https://m.youtube.com/watch?v=X6Ilrw32EKI

Diamond vs Graphite (Donald Sadoway, MIT)

"Network Wanderings in Paris" A summary of some of the great talks at #NetSci2018: https://t.co/UCNQsxncoD.

🌀 https://softbites.org/2018/06/22/a-storm-of-oscillators/amp/?__twitter_impression=true

#اطلاع_رسانی_سمینارهای_دانشکده
#سمينار_فيزیک_آماری #سمینار_ماده_چگال_نرم
امروز آقای متئو مارسیلی از عبدالسلام سخنرانی‌ با موضوع زیر ارائه می‌دهند.(یکشنبه سوم تیر ساعت ۱۵:۰۰ اتاق ۴۱۲ تالار پرتوی)

How simple are simple spin models?

The talk is about spin Hamiltonians with interactions of arbitrary order. An information
theoretic classification of these models into complexity classes will be discussed. The
results show that the information theoretic notion of a ``simple model’’ conforms to the
one assumed in physics. Applications to high dimensional inference will also be
discussed.

@anjoman_elmi_phys_sut

♦️ آزمایشگاه ملی نقشه برداری مغز برگزار میکند:

🔹دومین کارگاه مبانی پردازش سیگنالهای حیاتی با نرم افزار متلب با محوریت علوم اعصاب محاسباتی

🔹 اطلاعات بیشتر و ثبت نام در:
https://goo.gl/Xi13Tk

Claudio Castellano' slides on #spreading_processes on complex networks.
24th Annual #IASBS Meeting on Condensed Matter Physics & School on Complex Systems.

👌 Graph-tool is an efficient Python module for manipulation and statistical analysis of graphs (a.k.a. networks). Contrary to most other python modules with similar functionality, the core data structures and algorithms are implemented in C++, making extensive use of template metaprogramming, based heavily on the Boost Graph Library. This confers it a level of performance that is comparable (both in memory usage and computation time) to that of a pure C/C++ library.

https://graph-tool.skewed.de/

🌀 "A data scientist is a statistician who lives in San Francisco"

What’s the Difference Between Data Science and Statistics?

https://t.co/7zHlPKNf5u

🌀 به مناسبت تولد ۲۰سالگی مقاله واتس و استروگتز:

«بیست سال علم شبکه»

http://www.sitpor.org/2018/06/twenty-years-of-network-science/

🎞 "The Trouble With Community Detection."

metadata, statistical inference, the mirage of "ground truth", and community detection's No Free Lunch theorem.
https://www.aparat.com/v/QPnsm
https://youtu.be/cWFhxiRmHPo

دومین همایش مرزهای علوم‌زیستی
2 الی 4 مرداد 1397
http://biofrontiers.ipm.ir/

Here's a curious property of Brownian motion: it will fill out the whole space in 1D (a line), 2D (a sheet), but it can't fill a 3D or higher space.

https://t.co/kGDhOOFEJC

Are most systems really organized into scale-free networks? A new paper has cracked open a raging argument in network science.
https://t.co/aJJmWSLETo