Tiago Peixoto @tiago@social.skewed.de
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Admin
Network systems, data, and methods, using physics and statistical inference.
Associate Professor at DNDS/CEU, Vienna, Austria
Joined Aug 2018
Pinned toot
New version of graph-tool is out!
https://graph-tool.skewed.de
(New: https://graph-tool.skewed.de/static/doc/demos/inference/inference.html#latent-triadic-closures)
Single-line install instructions:
Anaconda ⤵️
conda create --name gt -c conda-forge graph-tool
Homebrew ⤵️
brew install graph-tool
Debian/Ubuntu⤵️
apt-get install python3-graph-tool
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RT @tiagopeixoto@twitter.com
I'm happy to announce a new project, called Netzschleuder: https://networks.skewed.de
This is a network data catalogue and repository. It currently contains 257 datasets totaling 3,916 individual networks (94,956 if you include a big @openstreetmap@twitter.com trove).
1/5
🐦🔗: https://twitter.com/tiagopeixoto/status/1306521483292872704
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New on the @arxiv_physics: "Disentangling homophily, community structure and triadic closure in networks", https://arxiv.org/abs/2101.02510
Homophily/communities and triadic closure (triangles) are conflated properties in network analysis, and this method tells them apart.
RT @sees_lab@twitter.com
Our work on Bayesian machine scientists has been highlighted in @icreacommunity@twitter.com's scientific highlights for 2020! Happy to see our work among so many great scientific discoveries https://memoir.icrea.cat/scientific-highlights/building-machine-scientists/
A bit self-promotional, but refreshingly understated! Subscribed.
RT @PiratePeel@twitter.com
Everyone seems to have a podcast these days, so I figured it was time I had one too.
You can check out episode 1 here: https://youtu.be/o6j5yPvhtjA
Enjoy!
🐦🔗: https://twitter.com/PiratePeel/status/1385314988324233216
RT @_jgyou@twitter.com
Last chance to get your abstracts in for SINM2021! 🕓 https://twitter.com/tiagopeixoto/status/1384106502118682624
Enough said! Subscribed.
RT @PiratePeel@twitter.com
Everyone seems to have a podcast these days, so I figured it was time I had one too.
You can check out episode 1 here: https://youtu.be/o6j5yPvhtjA
Enjoy!
🐦🔗: https://twitter.com/PiratePeel/status/1385314988324233216
Subscribed.
RT @PiratePeel@twitter.com
Everyone seems to have a podcast these days, so I figured it was time I had one too.
You can check out episode 1 here: https://youtu.be/o6j5yPvhtjA
Enjoy!
🐦🔗: https://twitter.com/PiratePeel/status/1385314988324233216
Microsoft does not really implement any sort of meaningful data protection; they just have the lawyer power to claim compliance. Choosing a Free alternative means that the institution needs to cover the liability itself... The end result is negative for data protection.
This reminds me of one of the negative outcomes of GDPR, where institutions migrate to Microsoft services because they provide GDPR certification, instead of overwhelmingly superior Free and Open Source alternatives (w.r.t data protection and everything else).
RT @cesifoti@twitter.com
High risk-systems will need to be registered in a centralized EU database, and also, include post-market monitoring systems. This is a lot of work. So a likely outcome is for large companies to hire specialized firms, or develop in-house teams, to produce such documentation. /15
So, there was a 4.4 magnitude earthquake in Vienna last night.
I felt it, but I thought I imagined it. Then I saw it in the news this morning.
I didn't know this was a thing in Austria.
Of course, the model is very likely to be misspecified (the SBM surely is), in which case it cannot really extract the true generative process, which leads to degenerate landscapes, etc. But the *end goal* is indeed to come as close as possible to extracting it. 7/8
A good inference method will tell the non-obvious. For example, if the network is fully random, the SBM inference tells you that there are no clusters --- even if the spring-block layout (or modularity maximization) indicates otherwise. 6/8
But I have to push back against the criticism of the "extraction" rhetoric. If you are fitting a generative model to a network, however simplistic, like the SBM, you are attempting indeed to extract something that lies behind the data --- the process that generated it. 5/8
Spring-block layouts only really tell you about assortative structures. Other mixing patterns (e.g. disassortativity) are completely obscured. Try drawing a bipartite network, and you get a complete hairball. It's an extremely biased instrument. But a lot of this is covered. 4/8
I do wonder if in the end @jacomyma@twitter.com is not over-interpreting these spring-block layouts (or as some call them, "ridiculograms"), but I found the overall analysis interesting, even if some of the social sciences/digital humanities discourse seems rather foreign to me. 3/8
I tend to use network visualizations in my work mainly as illustrations that take second plane to more principled methodology: the numbers give you the answer, not the picture. The picture just helps you to understand the numbers, but should not be taken too seriously. 2/8
This is a very interesting work from @jacomyma@twitter.com, the creator of @Gephi@twitter.com, about network visualization!
He articulates many ideas about network visualization, from a point of view that is very new to me. I have not read it all yet but I'm enjoying it. 1/8
RT @jacomyma@twitter.com
My PhD thesis is titled Situating Visual Network Analysis, and I will defend it June the 1st at 12:00 CET in Copenhagen. It will be accessible to an online audience. I will provide additional details when I have them.
Download: https://reticular.hypotheses.org/1879
RT @dnds_ceu@twitter.com
New year, new Data Stories exhibition @ceu@twitter.com! Submit your awesome research/data visualizations! Fantastic opportunity to showcase your most important findings, reveal a novel perspective on an old problem, connect dots that haven't been connected before: https://datastoriesceu.org/
RT @DirkBrockmann@twitter.com
Wer meine covid-19 statement Dauerschleife nicht mehr hören kann (so wie ich): hier ist mal was anderes. Kein covid-19. Versprochen. Wir reden über Kooperation in der Natur.
👇👇👇 https://twitter.com/suneman/status/1384136034678571010
🐦🔗: https://twitter.com/DirkBrockmann/status/1384141021735395335
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- 0x612DEFB798507F25
Admin
Network systems, data, and methods, using physics and statistical inference.
Associate Professor at DNDS/CEU, Vienna, Austria
Joined Aug 2018
