In large, highly connected networks where any vertex is very unlikely to be the sole connection between 2 or more parts of a network, could you functionally consider vertices with particularly high betweenness centrality, relative to the rest of the network, to be "bridge" vertices? I.e. vertices which, if removed, wouldn't *completely* disconnect parts of a network, but would *severely* reduce the connectedness between parts of a network? Or are the requirements for what you can consider a "bridge" vertex pretty narrowly and strictly defined when it comes to methods for analyzing them?
@ccb4723 ай бұрын
You are brilliant. Thank you for explaining this so clearly, and for simplifying with examples.
@yuliyaapukhtina43829 ай бұрын
Thank you Martin, that's one of most simple and in the same time comprehensive explanations of network analysis that I saw.
@JP-hu8ge10 ай бұрын
Thank u so much!
@-Skywalker01-11 ай бұрын
Very clear, good visualisation, right speed, thank you!
@saidycedano5775 Жыл бұрын
Hello, can you please offer a link to the Histograph Interface you mentioned at minute 4:24.. thank you!!!
@rubenfrancis95003 ай бұрын
Hello saidy, did you manage to find this software! its impossible to find but looks perfect
@BorisCristhianCaRomeroSuarez Жыл бұрын
Hi, nice presentation. Can you tell me, what font did you use on your document?
@MartinGrandjean Жыл бұрын
It's Optima :)
@gonzalorenatoquintanazunin6984 Жыл бұрын
What a great introductory course. Thank you so much!
@BioSlayer111 Жыл бұрын
Great touching on temporality. A network is a snapshot frozen in time. If you think of Time as an emergent physical property, not as a ticking clock, you can see a network evolves say through wiring and rewiring of nodes as they age and die at the experimental or theoretical rate you give them. Here differential and difference equations become handy for describing time equations for each node.
@ShahzadAli-sj5dp Жыл бұрын
is there any software available for social networking research
@petrusgimbad946 Жыл бұрын
Interesting - still above my head but can see the real world application and its uses.
@Alhamzah_F_Abbas Жыл бұрын
Very interesting workshop
@SMajid--SMajid Жыл бұрын
This is a great explanation of complicated concepts. Many others have complicated them further, thanks so much for such clear examples and simplification of concepts!
@prernamistri Жыл бұрын
wonderful video !
@AA-bs1ig Жыл бұрын
Hi , please how not create a redundunt path between 2 nodes already has a path.
@reijin999 Жыл бұрын
excellent video thank you
@baharataei11262 жыл бұрын
How can I add my xlsx data in here instead of writing it
@jenS.2832 жыл бұрын
thank you very much
@mghamari632 жыл бұрын
Perfect presentation! I am pretty new in this area. Two questions: A:What does distance mean in a network and how it is measured? B: How can we read a complex network? I mean is there always a matrix (matrices) behind every galaxy-form network like what you showed at 10:50? Thank you!
@MartinGrandjean2 жыл бұрын
Thank you for your questions. In a network, the distance refers to the number of nodes, that you need to go through from node A to node B (think about a metro map where you count the number of stops), the visual distance between the nodes in the visualisation is not meaningful, it's just the result of the spatialisation algorithm. And yes, there's alway a matrix behind a graph, even a very large one, but you'd often simplify it as an adjacency list because the adjacency matrix contains looots of empty cells (you rarely have a graph where all pairs of nodes are connected).
@mghamari632 жыл бұрын
@@MartinGrandjean Thank you for your reply! Can I have you email address please?
@mghamari632 жыл бұрын
@@MartinGrandjean How can we evaluate the accuracy of an inferred network? or How do we know that the constructed network accurately representing the interactions between entities? Thank you!
@MartinGrandjean2 жыл бұрын
@@mghamari63 I don't think I'm talking about inferred networks in this video. It's something that's intimately related to the discipline, the type of data, and the specific situation, so there's no general answer to that question. I feel like you have to compare it to other networks of the same type, or to a representative sample. But in history (which is the context of this video), we rarely use networks that aren't exactly the data we have (this has biases, but at least we know exactly what we're talking about).
@anapauladonate2 жыл бұрын
Congratulations!
@rodrigo100kk2 жыл бұрын
Very interesting subject. Very good explanation. Is there a business application to this ? Myb help product creators/sellers to understand where their audience is and how they are linked throughout social media.
@adrianmaulanamuhammad72252 жыл бұрын
Do you have a reference or source where the metrics are fully explained? I still have questions, like are we need to calculate all the metrics (avg path length, diameter, avg degree, etc.) or we can caculate a few metrics? How many metrics are enough to represent a network? Thanks
@mghamari632 жыл бұрын
@@MartinGrandjean The link of "Translating Networks" does not work. Would you share it again? Thank you!
@MartinGrandjean Жыл бұрын
@@mghamari63 Sorry for checking the comments this late, we’ll in fact KZbin added the ) at the end of the URL as if it was part of the link. I just removed it and think I works now.
@muskduh2 жыл бұрын
Thank you for all of your content!
@muskduh2 жыл бұрын
Thanks again!
@MCPetruk2 жыл бұрын
I don't understand his explanation of Euler.
@abolfazlmohebbi21042 жыл бұрын
It was a really informative and useful video series. Thanks a lot for that. However, as a novice person in this field, I realized the series was more focused on "Visualization" rather than "Analysis". Hence, I think the title of the videos can be a bit misleading.
@MartinGrandjean2 жыл бұрын
Hi, thank you for your feedback. You're right, this video series was initially meant to be used in a conference focused on history (HNR), a discipline that relies heavily on visualisation for network interpretation. The title made sense in this context, and this is by the way only an "introduction": I find always easier to use the visual approach to make people that are completely new to these methods understand what network analysis is (and then move to some more technical things on metrics, analysis, etc.).
@movimientoinformativo53142 жыл бұрын
where can i look for more information about this?
@movimientoinformativo53142 жыл бұрын
good job
@movimientoinformativo53142 жыл бұрын
excellent
@elisedermineur57782 жыл бұрын
What software would you use for creating a multi-layered network?
@muskduh2 жыл бұрын
this is great! thanks for building bridges for us
@MartinGrandjean2 жыл бұрын
Thank you, I'm happy if it can be helpful!
@RuhollahHosni2 жыл бұрын
UNDERSTANDING ME UNDERSTANDING YOU
@donharris88462 жыл бұрын
Great explanation. Well done
@MartinGrandjean2 жыл бұрын
Many thanks for your feedback!
@Sophieseee2 жыл бұрын
Un Super Grand merci! This series of lectures was very informative and clear - especially for someone who is not in the Historical field. The concepts were clear and very transferrable into my area of marine ecology :D fingers crossed I get to try this out!
@MartinGrandjean2 жыл бұрын
Merci ! Good luck for the application to your field (yes, the basics are valid for all disciplines)
@murilopalomosebilla29992 жыл бұрын
Really well presented! Thanks!!
@MartinGrandjean2 жыл бұрын
Thank you for the feedback!
@Splines3 жыл бұрын
Thank you so much Martin Grandjean for this great introductory series. The graphics were beautiful and really helped to emphasize and understand the points you made. I think it's really important to gather a basic understanding of the problem first and have a strong motivation and also see how this field of science evolved over time and how it started. You definitely reached your goal to make me think and dive deeper.
@MartinGrandjean2 жыл бұрын
Many thanks for your nice feedback! Cool, I hope you'll succeed in your deeper dive and your network analysis projects