Modeling Group Behavior

Data Skeptic

#Data Science #Datamining #Datascience #Machinelearning #Statistics #Kyle Polich #Science #Math #Tech #Skeptic

34:01

I think you could probably go back and track the stages of grief, probably that is what I went through. But I think if you do it right, you end up at acceptance. And that's where I ended up. And that's not to say that I've fully accepted the idea that the golden toad is extinct. Personally, I do still hold out hope that it could still be out there in those forests." - Trevor Ritland This conversation is with Trevor Ritland, who—along with his twin brother Kyle—authored The Golden Toad . The book chronicles their remarkable journey into Costa Rica’s cloud forest, once home to hundreds of brilliant golden toads that would emerge for just a few weeks each year—until, one day, they vanished without a trace. What began as a search for a lost species soon became something much more profound: a confrontation with ecological grief, a meditation on hope, and a powerful call to protect the natural world while we still can. Links: SpeciesUnite.com Kyle and Trevor: https://kyleandtrevor.com/ Instagram: https://www.instagram.com/adventureterm/ Goodreads - https://www.goodreads.com/book/show/222249677-the-golden-toad Amazon - https://www.amazon.com/Golden-Toad-Ecological-Mystery-Species/dp/163576996…

about a year ago 40:48

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Our guest in this episode is Sebastien Motsch, an assistant professor at Arizona State University, working in the School of Mathematical and Statistical Science. He works on modeling self-organized biological systems to understand how complex patterns emerge.

585 episodes

Modeling Group Behavior

Data Skeptic

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published about a year ago

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585 episodes

#Data Science #Datamining #Datascience #Machinelearning #Statistics #Kyle Polich #Science #Math #Tech #Skeptic

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Data Skeptic

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The Network Diversion Problem 46:14

1 day ago46:14

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In this episode, Professor Pål Grønås Drange from the University of Bergen, introduces the field of Parameterized Complexity - a powerful framework for tackling hard computational problems by focusing on specific structural aspects of the input. This framework allows researchers to solve NP-complete problems more efficiently when certain parameters, like the structure of the graph, are "well-behaved". At the center of the discussion is the network diversion problem, where the goal isn’t to block all routes between two points in a network, but to force flow - such as traffic, electricity, or data - through a specific path. While this problem appears deceptively similar to the classic "Min.Cut/Max.Flow" algorithm, it turns out to be much harder and, in general, its complexity is still unknown. Parameterized complexity plays a key role here by offering ways to make the problem tractable under constraints like low treewidth or planarity, which often exist in real-world networks like road systems or utility grids. Listeners will learn how vulnerability measures help identify weak points in networks, such as geopolitical infrastructure (e.g., gas pipelines like Nord Stream). Follow out guest: Pål Grønås Drange…

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Complex Dynamic in Networks 56:00

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Github Network Analysis 36:46

16 days ago36:46

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Networks and Complexity 17:49

25 days ago17:49

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Data Skeptic

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Actantial Networks 37:34

5 weeks ago37:34

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In this episode, listeners will learn about Actantial Networks—graph-based representations of narratives where nodes are actors (such as people, institutions, or abstract entities) and edges represent the actions or relationships between them. The one who will present these networks is our guest Armin Pournaki, a joint PhD candidate at the Max Planck Institute for Mathematics in the Sciences and the Laboratoire Lattice (ENS-PSL), who specializes in computational social science, where he develops methods to extract and analyze political narratives using natural language processing and network science. Armin explains how these methods can expose conflicting narratives around the same events, as seen in debates on COVID-19, climate change, or the war in Ukraine. Listeners will also discover how this approach helps make large-scale discourse—from millions of tweets or political speeches—more transparent and interpretable, offering tools for studying polarization, issue alignment, and narrative-driven persuasion in digital societies. Follow our guest Armin Pournaki's Webpage Twitter/X Bluesky Papers in focus How influencers and multipliers drive polarization and issue alignment on Twitter/X, 2025 A graph-based approach to extracting narrative signals from public discourse, 2024…

Data Skeptic

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Graphs for Causal AI 41:00

6 weeks ago41:00

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Data Skeptic

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