-
Network theory - Marc Samet
View full lesson: http://ed.ted.com/lessons/what-facebook-and-the-flu-have-in-common-marc-samet
From social media to massive financial institutions, we live within a web of networks. But how do they work? How does Googling a single word provide millions of results? Marc Samet investigates how these networks keep us connected and how they remain "alive."
Lesson by Marc Samet, animation by Thinkmore Studios.
published: 23 Jan 2013
-
The hidden networks of everything | Albert-László Barabási
This interview is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @JohnTempletonFoundation.
Subscribe to The Well on YouTube ► https://bit.ly/thewell-youtube
Watch Albert-László Barabási’s next interview ► https://youtu.be/E1eo80fFblM
Our world is filled with an abundance of data. Albert-László Barabási, a network scientist, believes that understanding the underlying structure and relationships of complex systems is crucial. Barabási’s research has challenged the notion of random connections and led to the discovery of a more accurate representation of how these systems are organized.
Barabási’s exploration began with the vast internet. Surprisingly, he found that the intricate web of connections did not follow random patterns but ...
published: 15 Jun 2023
-
Network Theory: The study of relationships
If you'd like to support these videos:
https://www.patreon.com/NotDavid
Network theory is the study of relationships - whether it be connections between characters in your fravourite TV show, real people, computers, or anything. Here we take a guided tour of what networks are, how they arise in nature, and what they can teach us.
I am trying to aim for quality over quantity with these videos. If you want to support the channel consider checking out my patreon: patreon.com/NotDavid
CITATIONS/ FOOTNOTES:
1. 3:15 Fragility of a network can be defined by the quantiative and qualitative changes in the network structure due to the removal of one or many nodes (or links). This can be done randomly or in a targeted fasion. A ring network is susceptible to both. Something like a small world net...
published: 28 May 2022
-
Network Theory Overview
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
A short overview to the new area of network theory.
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
published: 02 May 2014
-
Network Theory Overview
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
In this module we will give an overview to the different questions that we are interested in trying to answer when it comes to analysing networks, this module also works as an overview to the content we will be covering during the rest of the course.
Transcription:
In this section we are going to give an overview to network theory that will also work as an overview to the structure of this course and the content we will be covering. As the name implies network theory is all about the study of networks, we are trying to create models so as to analyze them, in order to be able to do this the first thing we need is some kind of formal l...
published: 16 Apr 2015
-
A gentle introduction to network science: Dr Renaud Lambiotte, University of Oxford
The language of networks and graphs has become a ubiquitous tool to analyse systems in domains ranging from biology to physics and from computer science to sociology. Renaud will present important properties observed in real-life networked systems, as well as tools to understand and model their structures.
#datascienceclasses
published: 13 Mar 2018
-
Network Theory (Ultimate Classroom lesson)
Here's an excerpt of the second lesson I gave to the teams during Episode 3 of Ultimate Classroom!
Find out more about the show here: https://10play.com.au/ultimate-classroom
More resources available at www.misterwootube.com
published: 29 Sep 2022
-
Mission Generation & Transmission (Network 1)
#genco #transco #mspgcl #msetcl #mseb
WhatsApp: wa.me/+919657659195
Telegram: https://t.me/KENDREINSTITUTE1
#ITIINSTRUCTOR #PCMCJE #SSCJE #MESMAINS
#mseb #msetcl #msedcl #mspgcl #Transco #discom #electrical #electricalengineering #महावितरण #महापारेषण #महानिर्मती #ITI #ELECTRICIAN #WIREMAN #PCMC #ITIINSTRUCTOR #DRDO #GAIL #TRANSCO
published: 11 Dec 2022
-
I Made a Graph From My Subscribers to Prove You’re Nerds
If you'd like to support these videos:
https://www.patreon.com/NotDavid
This is definitly the most effort and mathematics I've ever put into calling someone a nerd. I hope you enjoyed it! I also didn't know about this until it was pointed out to me, but https://youtubeatlas.com has a very similar network to mine. Our networks were made differently but conceptually are similar. Highly recommend you check it out!
Made using #blender as well as Davinci Resolve and Gephi.
DISCLAIMER: My channel is not endorsed by nor associated with any individuals, creators, or organizations featured in this video.
But also I hope that anyone that was included interprates their inclusion as a sign of my appriciation for their content.
Creators included (whose names were not explicitly written on screen)...
published: 21 Oct 2023
-
NETWORK THEORY | CIRCUITS AND NETWORKS | KTU ECT 205 | EET 201 | Circuit Theory| Malayalam | 2024
Download our app on android for full classes - https://play.google.com/store/apps/details?id=in.mgate.msigma
Network theory or circuits and networks will become easiest subject , if you study in this manner. This video is to provide a brief introduction of circuit theory. This class is enough for studying Network theory or circuits and networks for any university in India. its absolutely concept wise class rather than following a special syllabus. So any students from any university can score minimum of 85% mark in their respective university exams.
#circuittheory
#networktheory
#introtonetworktheorems
#circuitsandnetworks
#networktheory
#msigma
#msigmagokulam
#manusir
published: 16 Jul 2022
3:31
Network theory - Marc Samet
View full lesson: http://ed.ted.com/lessons/what-facebook-and-the-flu-have-in-common-marc-samet
From social media to massive financial institutions, we live wi...
View full lesson: http://ed.ted.com/lessons/what-facebook-and-the-flu-have-in-common-marc-samet
From social media to massive financial institutions, we live within a web of networks. But how do they work? How does Googling a single word provide millions of results? Marc Samet investigates how these networks keep us connected and how they remain "alive."
Lesson by Marc Samet, animation by Thinkmore Studios.
https://wn.com/Network_Theory_Marc_Samet
View full lesson: http://ed.ted.com/lessons/what-facebook-and-the-flu-have-in-common-marc-samet
From social media to massive financial institutions, we live within a web of networks. But how do they work? How does Googling a single word provide millions of results? Marc Samet investigates how these networks keep us connected and how they remain "alive."
Lesson by Marc Samet, animation by Thinkmore Studios.
- published: 23 Jan 2013
- views: 217506
7:28
The hidden networks of everything | Albert-László Barabási
This interview is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @JohnTempletonFoundation.
Subscribe t...
This interview is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @JohnTempletonFoundation.
Subscribe to The Well on YouTube ► https://bit.ly/thewell-youtube
Watch Albert-László Barabási’s next interview ► https://youtu.be/E1eo80fFblM
Our world is filled with an abundance of data. Albert-László Barabási, a network scientist, believes that understanding the underlying structure and relationships of complex systems is crucial. Barabási’s research has challenged the notion of random connections and led to the discovery of a more accurate representation of how these systems are organized.
Barabási’s exploration began with the vast internet. Surprisingly, he found that the intricate web of connections did not follow random patterns but instead followed a power load distribution. He named these networks “scale-free networks.”
Barabási’s groundbreaking work reveals that new connections in our networks tend to form with already well-connected elements. Scale-free networks exist in various complex systems, such as cellular interactions and social networks. This discovery is an important step toward comprehending the remarkable complexity that arises from countless interactions among the world’s many components.
0:00 Networks: How the world works
1:23 The theory of random graphs
3:15 What is network science?
6:49 Complex systems
Read the video transcript ► https://bigthink.com/the-well/decoding-our-world-graph-theory-networks?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
----------------------------------------------------------------------------------
About Albert-László Barabási:
Albert-László Barabási is a network scientist, fascinated with a wide range of topics, from unveiling the structure of the brain and treating diseases using network medicine to the emergence of success in art and how science really works. His research has helped unveil the hidden order behind various complex systems using the quantitative tools of network science, a research field that he pioneered, and has led to the discovery of scale-free networks, helping explain the emergence of many natural, technological, and social networks.
Barabási is a Fellow of the American Physical Society. He is the author of The Formula (Little Brown), Network Science (Cambridge), Bursts (Dutton), and Linked (Penguin). He co-edited Network Medicine (Harvard, 2017) and The Structure and Dynamics of Networks (Princeton, 2005). His books have been translated into over twenty languages.
----------------------------------------------------------------------------------
Read more from The Well:
Eastern philosophy says there is no “self.” Science agrees
► https://bigthink.com/the-well/eastern-philosophy-neuroscience-no-self/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
I’m “spiritual but not religious.” Here’s what that means for a physicist
► https://bigthink.com/the-well/spiritual-not-religious-physicist/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
Groupthink is for mindless pawns, but group thinking will push humanity further
► https://bigthink.com/the-well/groupthink-vs-group-thinking/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
When do humans become conscious — in the womb or after birth?
----------------------------------------------------------------------------------
About The Well
Do we inhabit a multiverse? Do we have free will? What is love? Is evolution directional? There are no simple answers to life’s biggest questions, and that’s why they’re the questions occupying the world’s brightest minds.
Together, let's learn from them.
Subscribe to the weekly newsletter ► https://bit.ly/thewellemailsignup
----------------------------------------------------------------------------------
Join The Well on your favorite platforms:
► Facebook: https://bit.ly/thewellFB
► Instagram: https://bit.ly/thewellIG
https://wn.com/The_Hidden_Networks_Of_Everything_|_Albert_László_Barabási
This interview is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @JohnTempletonFoundation.
Subscribe to The Well on YouTube ► https://bit.ly/thewell-youtube
Watch Albert-László Barabási’s next interview ► https://youtu.be/E1eo80fFblM
Our world is filled with an abundance of data. Albert-László Barabási, a network scientist, believes that understanding the underlying structure and relationships of complex systems is crucial. Barabási’s research has challenged the notion of random connections and led to the discovery of a more accurate representation of how these systems are organized.
Barabási’s exploration began with the vast internet. Surprisingly, he found that the intricate web of connections did not follow random patterns but instead followed a power load distribution. He named these networks “scale-free networks.”
Barabási’s groundbreaking work reveals that new connections in our networks tend to form with already well-connected elements. Scale-free networks exist in various complex systems, such as cellular interactions and social networks. This discovery is an important step toward comprehending the remarkable complexity that arises from countless interactions among the world’s many components.
0:00 Networks: How the world works
1:23 The theory of random graphs
3:15 What is network science?
6:49 Complex systems
Read the video transcript ► https://bigthink.com/the-well/decoding-our-world-graph-theory-networks?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
----------------------------------------------------------------------------------
About Albert-László Barabási:
Albert-László Barabási is a network scientist, fascinated with a wide range of topics, from unveiling the structure of the brain and treating diseases using network medicine to the emergence of success in art and how science really works. His research has helped unveil the hidden order behind various complex systems using the quantitative tools of network science, a research field that he pioneered, and has led to the discovery of scale-free networks, helping explain the emergence of many natural, technological, and social networks.
Barabási is a Fellow of the American Physical Society. He is the author of The Formula (Little Brown), Network Science (Cambridge), Bursts (Dutton), and Linked (Penguin). He co-edited Network Medicine (Harvard, 2017) and The Structure and Dynamics of Networks (Princeton, 2005). His books have been translated into over twenty languages.
----------------------------------------------------------------------------------
Read more from The Well:
Eastern philosophy says there is no “self.” Science agrees
► https://bigthink.com/the-well/eastern-philosophy-neuroscience-no-self/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
I’m “spiritual but not religious.” Here’s what that means for a physicist
► https://bigthink.com/the-well/spiritual-not-religious-physicist/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
Groupthink is for mindless pawns, but group thinking will push humanity further
► https://bigthink.com/the-well/groupthink-vs-group-thinking/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
When do humans become conscious — in the womb or after birth?
----------------------------------------------------------------------------------
About The Well
Do we inhabit a multiverse? Do we have free will? What is love? Is evolution directional? There are no simple answers to life’s biggest questions, and that’s why they’re the questions occupying the world’s brightest minds.
Together, let's learn from them.
Subscribe to the weekly newsletter ► https://bit.ly/thewellemailsignup
----------------------------------------------------------------------------------
Join The Well on your favorite platforms:
► Facebook: https://bit.ly/thewellFB
► Instagram: https://bit.ly/thewellIG
- published: 15 Jun 2023
- views: 185194
9:20
Network Theory: The study of relationships
If you'd like to support these videos:
https://www.patreon.com/NotDavid
Network theory is the study of relationships - whether it be connections between charac...
If you'd like to support these videos:
https://www.patreon.com/NotDavid
Network theory is the study of relationships - whether it be connections between characters in your fravourite TV show, real people, computers, or anything. Here we take a guided tour of what networks are, how they arise in nature, and what they can teach us.
I am trying to aim for quality over quantity with these videos. If you want to support the channel consider checking out my patreon: patreon.com/NotDavid
CITATIONS/ FOOTNOTES:
1. 3:15 Fragility of a network can be defined by the quantiative and qualitative changes in the network structure due to the removal of one or many nodes (or links). This can be done randomly or in a targeted fasion. A ring network is susceptible to both. Something like a small world network (defined later in the video) is susceptible to targeted removal of nodes but not random removal of nodes. This is an important consideration in critical infrastructure networks (power grids, internet, etc.).
2. 3:54 This is optimistic as I only considered unweighted undirected networks. For either directed or weighted networks, this number would expload even faster. Don't worry if this doesn't mean anything to you though.
3. 4:19 The two graphs on the left are called "random" networks (which will potentially be a future topic) where as the one on the right is potentially a small world network.
4. 4:44 In network neuroscience there is the distinction between structural networks (e.g., following the connections of physical neurons or brain regions) or functional networks (e.g., formed by looking at which neurons activate together). We will touch on this more in a future video on network inference.
5. 5:15 6 Degrees of Seperation and the Kevin Bacon number are really the same thing more or less. There are also a lot of problems with the original 6 Degrees of Seperation experiment, which we will touch on in the network inference video in the future.
6. 5:26 This is not a rigerous definition of small world networks. Typically one has to consider whats called the average path length, and how it scales as a function of the number of nodes. In many real world systems though this is difficult to do as you can't simply add nodes.
7. 5:42 For example, for the year of 2019, 15 airports accounted for 10% of world wide travel, despite the fact that they only acount for 0.03% of airports.
8. 6:16 Its a bit more complicated this as these are actually typically formed by what are called hyper-networks or hypergraphs where in we have different types of nodes. You wouldn't want a purely small world network because, as mentioned in citation 1, small world networks are susceptible to targeted network attacks.
9. 6:27 Paper: "Emergence of a Small-World Functional Network in Cultured Neurons"
Julia H. Downes et. al.
and
"Self-organization of in vitro neuronal assemblies drives to complex network topology"
Prciscila C. Antonello et. al.
(the second has a preprint on Biorxiv and should be free to access there)
10. 7:01 Much of this analysis has been attributed to Jacob Moreno, though it appears that the majority (if not all) of this work was conducted by his assistant Helen Hall Jennings as Moreno was not mathematically motivated nor was he particularly interested in systematic research. Unfortunently this is not uncommon in science.
Footnote 7:50 -- Bojack Horseman
11. 8:06 If you're interested in more, Networks: An Introduction by Mark Newman is a great introduction into the field.
12. This is from Evalina Gabasova's 2015 blog entry "The star wars social network" (you should be able to just google that), I highly recommend it. I unfortunently was not able to find the kpop group network again. If I find it in the future I'll edit this.
CREDITS:
Most assets created by myself.
-The brain model is by Anderson Winkle, licensed under Creative Commons Attribution-ShareAlike 3.0 Unported License. The original work can be found at https://brainder.org/brain-for-blender
Notable tutorials used:
- Making (Procedural) Membranes | Blender for Biochemists | Geometry Nodes by Brady Johnston
Special thanks to thebasemesh.com for providing some of the assets.
MUSIC (in order)
%%
- Loafy Building x Hoffy Beats – Sleepless Wonder
- Provided by Lofi Records
- Watch: https://youtu.be/6XI7A7SJ2MA
- Download/Stream: https://fanlink.to/HighFlying
📥 | Download this music (free)
→ https://lofigirl.com/blogs/releases/high-flying
%%
- Cauffee – Vague Familiarity
-https://www.youtube.com/watch?v=6-iNmocJsAM
%%
- Purrple Cat – Cold Pizza
- Provided by Lofi Records
- Watch: https://youtu.be/Kt5c-haAoxw
- Download/Stream: https://fanlink.to/DistantWorlds
📥 | Download this music (free)
→ https://lofigirl.com/blogs/releases/distant-worlds
%%
- Kevin McLeod/ Incompetech
-https://incompetech.com
%%
- Cauffee – Unreleased
https://wn.com/Network_Theory_The_Study_Of_Relationships
If you'd like to support these videos:
https://www.patreon.com/NotDavid
Network theory is the study of relationships - whether it be connections between characters in your fravourite TV show, real people, computers, or anything. Here we take a guided tour of what networks are, how they arise in nature, and what they can teach us.
I am trying to aim for quality over quantity with these videos. If you want to support the channel consider checking out my patreon: patreon.com/NotDavid
CITATIONS/ FOOTNOTES:
1. 3:15 Fragility of a network can be defined by the quantiative and qualitative changes in the network structure due to the removal of one or many nodes (or links). This can be done randomly or in a targeted fasion. A ring network is susceptible to both. Something like a small world network (defined later in the video) is susceptible to targeted removal of nodes but not random removal of nodes. This is an important consideration in critical infrastructure networks (power grids, internet, etc.).
2. 3:54 This is optimistic as I only considered unweighted undirected networks. For either directed or weighted networks, this number would expload even faster. Don't worry if this doesn't mean anything to you though.
3. 4:19 The two graphs on the left are called "random" networks (which will potentially be a future topic) where as the one on the right is potentially a small world network.
4. 4:44 In network neuroscience there is the distinction between structural networks (e.g., following the connections of physical neurons or brain regions) or functional networks (e.g., formed by looking at which neurons activate together). We will touch on this more in a future video on network inference.
5. 5:15 6 Degrees of Seperation and the Kevin Bacon number are really the same thing more or less. There are also a lot of problems with the original 6 Degrees of Seperation experiment, which we will touch on in the network inference video in the future.
6. 5:26 This is not a rigerous definition of small world networks. Typically one has to consider whats called the average path length, and how it scales as a function of the number of nodes. In many real world systems though this is difficult to do as you can't simply add nodes.
7. 5:42 For example, for the year of 2019, 15 airports accounted for 10% of world wide travel, despite the fact that they only acount for 0.03% of airports.
8. 6:16 Its a bit more complicated this as these are actually typically formed by what are called hyper-networks or hypergraphs where in we have different types of nodes. You wouldn't want a purely small world network because, as mentioned in citation 1, small world networks are susceptible to targeted network attacks.
9. 6:27 Paper: "Emergence of a Small-World Functional Network in Cultured Neurons"
Julia H. Downes et. al.
and
"Self-organization of in vitro neuronal assemblies drives to complex network topology"
Prciscila C. Antonello et. al.
(the second has a preprint on Biorxiv and should be free to access there)
10. 7:01 Much of this analysis has been attributed to Jacob Moreno, though it appears that the majority (if not all) of this work was conducted by his assistant Helen Hall Jennings as Moreno was not mathematically motivated nor was he particularly interested in systematic research. Unfortunently this is not uncommon in science.
Footnote 7:50 -- Bojack Horseman
11. 8:06 If you're interested in more, Networks: An Introduction by Mark Newman is a great introduction into the field.
12. This is from Evalina Gabasova's 2015 blog entry "The star wars social network" (you should be able to just google that), I highly recommend it. I unfortunently was not able to find the kpop group network again. If I find it in the future I'll edit this.
CREDITS:
Most assets created by myself.
-The brain model is by Anderson Winkle, licensed under Creative Commons Attribution-ShareAlike 3.0 Unported License. The original work can be found at https://brainder.org/brain-for-blender
Notable tutorials used:
- Making (Procedural) Membranes | Blender for Biochemists | Geometry Nodes by Brady Johnston
Special thanks to thebasemesh.com for providing some of the assets.
MUSIC (in order)
%%
- Loafy Building x Hoffy Beats – Sleepless Wonder
- Provided by Lofi Records
- Watch: https://youtu.be/6XI7A7SJ2MA
- Download/Stream: https://fanlink.to/HighFlying
📥 | Download this music (free)
→ https://lofigirl.com/blogs/releases/high-flying
%%
- Cauffee – Vague Familiarity
-https://www.youtube.com/watch?v=6-iNmocJsAM
%%
- Purrple Cat – Cold Pizza
- Provided by Lofi Records
- Watch: https://youtu.be/Kt5c-haAoxw
- Download/Stream: https://fanlink.to/DistantWorlds
📥 | Download this music (free)
→ https://lofigirl.com/blogs/releases/distant-worlds
%%
- Kevin McLeod/ Incompetech
-https://incompetech.com
%%
- Cauffee – Unreleased
- published: 28 May 2022
- views: 17224
5:31
Network Theory Overview
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
A short overview to the new area of network theory.
Twitter: http://...
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
A short overview to the new area of network theory.
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
https://wn.com/Network_Theory_Overview
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
A short overview to the new area of network theory.
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
- published: 02 May 2014
- views: 52989
5:50
Network Theory Overview
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
In thi...
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
In this module we will give an overview to the different questions that we are interested in trying to answer when it comes to analysing networks, this module also works as an overview to the content we will be covering during the rest of the course.
Transcription:
In this section we are going to give an overview to network theory that will also work as an overview to the structure of this course and the content we will be covering. As the name implies network theory is all about the study of networks, we are trying to create models so as to analyze them, in order to be able to do this the first thing we need is some kind of formal language and this formal language is called graph theory. We will be going into the details of graph theory in the next lecture but it is a relatively new area of mathematics that gives us some kind of standardized language with which to talk about and quantify the structure and properties of networks.
So once we have this basic vocabulary, say you give me a network to analyze the question then turns to what are the features and properties of this network that we should be really interested. The first set of questions we might like to ask relate to individual elements within the network. We want to know what are the nodes within the network what are the connections between them and what properties are we really interested in, for example in a computer network we might not be interested in who owns the different computers and connections but just interested in the speed of the computers and the bandwidth of the connections, so we need to define what it is about our network we are interested in because as with all models we will be focusing on some information and excluding other.
There is lots of other information we want to know about these individual elements and the connections, such as asking whether they are weighted or not, meaning can we ascribe a value to them, we can talk about a computer network’s bandwidth in megabits per second, but it might not be so easy to do the same with a social network where the relations are of friendship or kinship. We can also ask if these relations go both ways or are just unidirectional. Other questions we will be asking here is how connected is any individual node or how central is it within the overall network.
The next major set of questions we will be asking about our network will relate to its overall structure, networks are defined by both what happens on the local level, that is how central or connected you are, but also what happens on the global level, because the dynamics of the network on the global level feeds back to effect the elements on the local level.
Here some of the key questions we will be asking about the overall structure to the network is firstly how connected is it? Are there connections between all the parts or are some parts disconnect and separate from others? How dense is this set of connections? If we compare a group of unassociated people waiting at a bus stop with a close knit group of friends we will see the density of the network will vary greatly. What are the patters of clustering within the system? Do we see many small groups or just a few large groups? These are the types of features that will define the overall makeup of the network structure. One key question we are interested in answering here is if we change some parameter to one of
https://wn.com/Network_Theory_Overview
Take the full course: https://bit.ly/SiCourse
Download booklet: https://bit.ly/SiBooklets
Twitter: http://bit.ly/2JuNmXX
LinkedIn: http://bit.ly/2YCP2U6
In this module we will give an overview to the different questions that we are interested in trying to answer when it comes to analysing networks, this module also works as an overview to the content we will be covering during the rest of the course.
Transcription:
In this section we are going to give an overview to network theory that will also work as an overview to the structure of this course and the content we will be covering. As the name implies network theory is all about the study of networks, we are trying to create models so as to analyze them, in order to be able to do this the first thing we need is some kind of formal language and this formal language is called graph theory. We will be going into the details of graph theory in the next lecture but it is a relatively new area of mathematics that gives us some kind of standardized language with which to talk about and quantify the structure and properties of networks.
So once we have this basic vocabulary, say you give me a network to analyze the question then turns to what are the features and properties of this network that we should be really interested. The first set of questions we might like to ask relate to individual elements within the network. We want to know what are the nodes within the network what are the connections between them and what properties are we really interested in, for example in a computer network we might not be interested in who owns the different computers and connections but just interested in the speed of the computers and the bandwidth of the connections, so we need to define what it is about our network we are interested in because as with all models we will be focusing on some information and excluding other.
There is lots of other information we want to know about these individual elements and the connections, such as asking whether they are weighted or not, meaning can we ascribe a value to them, we can talk about a computer network’s bandwidth in megabits per second, but it might not be so easy to do the same with a social network where the relations are of friendship or kinship. We can also ask if these relations go both ways or are just unidirectional. Other questions we will be asking here is how connected is any individual node or how central is it within the overall network.
The next major set of questions we will be asking about our network will relate to its overall structure, networks are defined by both what happens on the local level, that is how central or connected you are, but also what happens on the global level, because the dynamics of the network on the global level feeds back to effect the elements on the local level.
Here some of the key questions we will be asking about the overall structure to the network is firstly how connected is it? Are there connections between all the parts or are some parts disconnect and separate from others? How dense is this set of connections? If we compare a group of unassociated people waiting at a bus stop with a close knit group of friends we will see the density of the network will vary greatly. What are the patters of clustering within the system? Do we see many small groups or just a few large groups? These are the types of features that will define the overall makeup of the network structure. One key question we are interested in answering here is if we change some parameter to one of
- published: 16 Apr 2015
- views: 51418
1:40:43
A gentle introduction to network science: Dr Renaud Lambiotte, University of Oxford
The language of networks and graphs has become a ubiquitous tool to analyse systems in domains ranging from biology to physics and from computer science to soci...
The language of networks and graphs has become a ubiquitous tool to analyse systems in domains ranging from biology to physics and from computer science to sociology. Renaud will present important properties observed in real-life networked systems, as well as tools to understand and model their structures.
#datascienceclasses
https://wn.com/A_Gentle_Introduction_To_Network_Science_Dr_Renaud_Lambiotte,_University_Of_Oxford
The language of networks and graphs has become a ubiquitous tool to analyse systems in domains ranging from biology to physics and from computer science to sociology. Renaud will present important properties observed in real-life networked systems, as well as tools to understand and model their structures.
#datascienceclasses
- published: 13 Mar 2018
- views: 58299
7:42
Network Theory (Ultimate Classroom lesson)
Here's an excerpt of the second lesson I gave to the teams during Episode 3 of Ultimate Classroom!
Find out more about the show here: https://10play.com.au/ult...
Here's an excerpt of the second lesson I gave to the teams during Episode 3 of Ultimate Classroom!
Find out more about the show here: https://10play.com.au/ultimate-classroom
More resources available at www.misterwootube.com
https://wn.com/Network_Theory_(Ultimate_Classroom_Lesson)
Here's an excerpt of the second lesson I gave to the teams during Episode 3 of Ultimate Classroom!
Find out more about the show here: https://10play.com.au/ultimate-classroom
More resources available at www.misterwootube.com
- published: 29 Sep 2022
- views: 17219
1:12:51
Mission Generation & Transmission (Network 1)
#genco #transco #mspgcl #msetcl #mseb
WhatsApp: wa.me/+919657659195
Telegram: https://t.me/KENDREINSTITUTE1
#ITIINSTRUCTOR #PCMCJE #SSCJE #MESMAINS
#mse...
#genco #transco #mspgcl #msetcl #mseb
WhatsApp: wa.me/+919657659195
Telegram: https://t.me/KENDREINSTITUTE1
#ITIINSTRUCTOR #PCMCJE #SSCJE #MESMAINS
#mseb #msetcl #msedcl #mspgcl #Transco #discom #electrical #electricalengineering #महावितरण #महापारेषण #महानिर्मती #ITI #ELECTRICIAN #WIREMAN #PCMC #ITIINSTRUCTOR #DRDO #GAIL #TRANSCO
https://wn.com/Mission_Generation_Transmission_(Network_1)
#genco #transco #mspgcl #msetcl #mseb
WhatsApp: wa.me/+919657659195
Telegram: https://t.me/KENDREINSTITUTE1
#ITIINSTRUCTOR #PCMCJE #SSCJE #MESMAINS
#mseb #msetcl #msedcl #mspgcl #Transco #discom #electrical #electricalengineering #महावितरण #महापारेषण #महानिर्मती #ITI #ELECTRICIAN #WIREMAN #PCMC #ITIINSTRUCTOR #DRDO #GAIL #TRANSCO
- published: 11 Dec 2022
- views: 50888
17:43
I Made a Graph From My Subscribers to Prove You’re Nerds
If you'd like to support these videos:
https://www.patreon.com/NotDavid
This is definitly the most effort and mathematics I've ever put into calling someone a ...
If you'd like to support these videos:
https://www.patreon.com/NotDavid
This is definitly the most effort and mathematics I've ever put into calling someone a nerd. I hope you enjoyed it! I also didn't know about this until it was pointed out to me, but https://youtubeatlas.com has a very similar network to mine. Our networks were made differently but conceptually are similar. Highly recommend you check it out!
Made using #blender as well as Davinci Resolve and Gephi.
DISCLAIMER: My channel is not endorsed by nor associated with any individuals, creators, or organizations featured in this video.
But also I hope that anyone that was included interprates their inclusion as a sign of my appriciation for their content.
Creators included (whose names were not explicitly written on screen):
Jenny Nicholson, Summoning Salt, Matthewmatosis, Technology Connections, Drawfee Show, Super Eyepatch Wolf, Jacob Geller, Hbomberguy, Folding Ideas, Legal Eagle, Polygon, Brian David Gilbert, Karolina Żebrowska, Bernadette Banner.
Content Featured:
The qoute at the end was taken from Matthewmatosis: https://youtu.be/PGv4ixLllWo?si=uKdMi6cHzibmbMuk
The speedruning video was featuring Darbian, but it was from the Summoning Salt channel:
https://youtu.be/udQ_XUJt34M?si=7q3JQOpoMhzODlVC
Chapters:
0:00 I need a hobby lol
1:38 Building the network
4:26 Who do you subscribe to?
6:46 co-subscribers and bots
9:29 Proving you're nerds
11:37 The Youtube network
14:20 The Youtube communities
Music (in order):
RPG Store - Chris Doerksen https://chrisdoerksen.bandcamp.com/album/looking-for-light
Native - HOME https://open.spotify.com/artist/2exebQUDoIoT0dXA8BcN1P?si=UVkY4Ix1SOekhSogJXXWSg
Killer Vacation - Chris Doerksen (see previous link)
Literally Chill - Florida Skyline https://floridaskyline.bandcamp.com
Intermission - Stux.io and Vaporwavez https://stuxio.bandcamp.com/album/quantum-superpositions-and-discrete-abstractions-premium-deluxe-edition
Vague Familiarity - Not David https://youtu.be/6-iNmocJsAM?si=29Yog8xOPy7Ri4X2
Atlas - HOME (see previous link)
Power Cycle - Kuraine/ Lena Raine https://radicaldreamland.bandcamp.com/album/singularity
Notes:
-Regarding the degree distribution and cutting it off abruptly - in actuality the fact that it is a straight line in log-log is really interesting, but that could be a video on its own so rather than going into it, I just decided to leave it as a joke because this is actually one of the things you would do first in a real network analysis.
-I didn't specify this but when I removed the weakest links from the co-citation network, I also removed any nodes that became disconnected from the network.
-In order to make the youtube network I had to play a bit of a trick. You see, the API does not (as far as I know) let me just randomly pick a user from youtube. Because of this, what I did was to get a random list of my subscribers. Then I get a random list of people that they subscribe to. Then I ask who do these people subscribe to, and that is how I build the network. Essentially I'm adding extra steps to the original method to "get away" from my subscribers. Because of this, it is also possible to get channels that do not subscribe to anyone, leading to an isolated node - these were discarded from the analysis.
- For the community detection the Louvain algorithm returns something like 140 communties. However, many of these are very small and while I didn't do additional testing, I doubt they would be statistically significant. These channels were removed from the animation so that I was left with only something like 8 fairly large communities. They were included in all the other analysis however, they just aren't rendered.
- I've put the co-subscriber network gephi file on github
https://github.com/notDavidsGit/notdavidcocitationnetwork
https://wn.com/I_Made_A_Graph_From_My_Subscribers_To_Prove_You’Re_Nerds
If you'd like to support these videos:
https://www.patreon.com/NotDavid
This is definitly the most effort and mathematics I've ever put into calling someone a nerd. I hope you enjoyed it! I also didn't know about this until it was pointed out to me, but https://youtubeatlas.com has a very similar network to mine. Our networks were made differently but conceptually are similar. Highly recommend you check it out!
Made using #blender as well as Davinci Resolve and Gephi.
DISCLAIMER: My channel is not endorsed by nor associated with any individuals, creators, or organizations featured in this video.
But also I hope that anyone that was included interprates their inclusion as a sign of my appriciation for their content.
Creators included (whose names were not explicitly written on screen):
Jenny Nicholson, Summoning Salt, Matthewmatosis, Technology Connections, Drawfee Show, Super Eyepatch Wolf, Jacob Geller, Hbomberguy, Folding Ideas, Legal Eagle, Polygon, Brian David Gilbert, Karolina Żebrowska, Bernadette Banner.
Content Featured:
The qoute at the end was taken from Matthewmatosis: https://youtu.be/PGv4ixLllWo?si=uKdMi6cHzibmbMuk
The speedruning video was featuring Darbian, but it was from the Summoning Salt channel:
https://youtu.be/udQ_XUJt34M?si=7q3JQOpoMhzODlVC
Chapters:
0:00 I need a hobby lol
1:38 Building the network
4:26 Who do you subscribe to?
6:46 co-subscribers and bots
9:29 Proving you're nerds
11:37 The Youtube network
14:20 The Youtube communities
Music (in order):
RPG Store - Chris Doerksen https://chrisdoerksen.bandcamp.com/album/looking-for-light
Native - HOME https://open.spotify.com/artist/2exebQUDoIoT0dXA8BcN1P?si=UVkY4Ix1SOekhSogJXXWSg
Killer Vacation - Chris Doerksen (see previous link)
Literally Chill - Florida Skyline https://floridaskyline.bandcamp.com
Intermission - Stux.io and Vaporwavez https://stuxio.bandcamp.com/album/quantum-superpositions-and-discrete-abstractions-premium-deluxe-edition
Vague Familiarity - Not David https://youtu.be/6-iNmocJsAM?si=29Yog8xOPy7Ri4X2
Atlas - HOME (see previous link)
Power Cycle - Kuraine/ Lena Raine https://radicaldreamland.bandcamp.com/album/singularity
Notes:
-Regarding the degree distribution and cutting it off abruptly - in actuality the fact that it is a straight line in log-log is really interesting, but that could be a video on its own so rather than going into it, I just decided to leave it as a joke because this is actually one of the things you would do first in a real network analysis.
-I didn't specify this but when I removed the weakest links from the co-citation network, I also removed any nodes that became disconnected from the network.
-In order to make the youtube network I had to play a bit of a trick. You see, the API does not (as far as I know) let me just randomly pick a user from youtube. Because of this, what I did was to get a random list of my subscribers. Then I get a random list of people that they subscribe to. Then I ask who do these people subscribe to, and that is how I build the network. Essentially I'm adding extra steps to the original method to "get away" from my subscribers. Because of this, it is also possible to get channels that do not subscribe to anyone, leading to an isolated node - these were discarded from the analysis.
- For the community detection the Louvain algorithm returns something like 140 communties. However, many of these are very small and while I didn't do additional testing, I doubt they would be statistically significant. These channels were removed from the animation so that I was left with only something like 8 fairly large communities. They were included in all the other analysis however, they just aren't rendered.
- I've put the co-subscriber network gephi file on github
https://github.com/notDavidsGit/notdavidcocitationnetwork
- published: 21 Oct 2023
- views: 342676
1:03:34
NETWORK THEORY | CIRCUITS AND NETWORKS | KTU ECT 205 | EET 201 | Circuit Theory| Malayalam | 2024
Download our app on android for full classes - https://play.google.com/store/apps/details?id=in.mgate.msigma
Network theory or circuits and networks will becom...
Download our app on android for full classes - https://play.google.com/store/apps/details?id=in.mgate.msigma
Network theory or circuits and networks will become easiest subject , if you study in this manner. This video is to provide a brief introduction of circuit theory. This class is enough for studying Network theory or circuits and networks for any university in India. its absolutely concept wise class rather than following a special syllabus. So any students from any university can score minimum of 85% mark in their respective university exams.
#circuittheory
#networktheory
#introtonetworktheorems
#circuitsandnetworks
#networktheory
#msigma
#msigmagokulam
#manusir
https://wn.com/Network_Theory_|_Circuits_And_Networks_|_Ktu_Ect_205_|_Eet_201_|_Circuit_Theory|_Malayalam_|_2024
Download our app on android for full classes - https://play.google.com/store/apps/details?id=in.mgate.msigma
Network theory or circuits and networks will become easiest subject , if you study in this manner. This video is to provide a brief introduction of circuit theory. This class is enough for studying Network theory or circuits and networks for any university in India. its absolutely concept wise class rather than following a special syllabus. So any students from any university can score minimum of 85% mark in their respective university exams.
#circuittheory
#networktheory
#introtonetworktheorems
#circuitsandnetworks
#networktheory
#msigma
#msigmagokulam
#manusir
- published: 16 Jul 2022
- views: 7064