NETfrix - Network Science Podcast

To make Network Analysis accessible, we'll learn about a free and popular Network Analysis Software called Gephi. In this episode, Gephi's founder, Mathieu Jacomy, will reveal new features and make you an offer you can't refuse if you're a Java developer 😊. In the next episode, we'll continue this survey with about a dozen more free Network Analysis Software. To help expand the SNA and Network Science community, NETfrix needs you...

This episode features Dr. Ann McCranie, the Chief Organizer, with special tips to newcomers & Prof. Baruch Barzel on his lab's presentation about new discoveries & mysteries of Network Dynamics. Transcript & Links: http://bit.ly/NETfrix_Networks2021Blog Rate NETfrix: http://bit.ly/Rate_Netfrix Follow on Twitter: https://bit.ly/netfrixP_Twitter

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Network Science and its dear friend, Data, are here to throw some of our intuitions about politics and partisanship under the nearest bus. Partisanship is Networks' nemesis: Networks are all about connecting while partisanship hacks away at the network's links… So, who shall prevail? SUBSCRIBE or review here: http://bit.ly/NETfrix_Review Transcripts are available on SNApod.net See you on the other side of NETfrix.

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Here we'll discuss why dynamic networks are chaotic and what are the implications and applications of this statement, especially, to the field of machine learning.   PLS review here: http://bit.ly/NETfrix_Review Transcripts are available on SNApod.net See you on the other side of NETfrix.

Dynamic networks are data science's Holy Grail. Here we'll learn why, and what are the applications and implications of dynamic networks.  To do so, we'll have to understand what it has to do with complex system, chaos theory and, of course, groundhogs. PLS review here: http://bit.ly/NETfrix_Review Transcripts are available on SNApod.net See you on the other side of NETfrix.

How to tell a story about data by using Community Detection in networks. Communities (or clusters) are the building blocks of all networks. In this episode we'll learn about their formation and special features, and how to apply this knowledge on Big Data. And I promise - your views about cauliflowers will never be the same.  PLS review here: http://bit.ly/NETfrix_Review Transcripts are available on SNApod.net See you on the othe...

In this episode we'll learn how to tell a story about data by using the network's gravity centers or hubs. We'll find out that hubs come in many forms and stem from different notions of what it means to be central in a network. We'll learn how to find them and how to apply this knowledge to many fields, like social media, advertising and... even on Game Of Thrones. No spoilers. PLS review here: http://bit.ly/NETfrix_Review Transc...

What do Facebook, Bitcoin and an ad campaign for designer glasses have in common? They all conform to Network Science laws. These laws are universal and are manifested in a n y network. Understanding these laws would change your perception of the world, and your data. I've warned you - Network Analysis is a powerful tool. Use it wisely - don't lose your head. PLS review here: http://bit.ly/NETfrix_Review

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Milgram, the famous researcher from the 60's, set out to find how small is our world and came back with the 6-degrees-of-separation slogan, meaning the human society's network is seemingly just 6 links in diameter. Why seemingly? Because we are going to find out that Milgram got it wrong and the truth about the network is even less intuitive than he imagined.  PLS review here: http://bit.ly/NETfrix_Review

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