Pol.is Graph Theoretic Modeling

--- title Pol.is Graph Theoretic Modeling description Formalizing the Pol.is graph --- # Pol.is Graph Theoretic Modeling [![hackmd-github-sync-badge](https://hackmd.io/96BFPSiRQtK78NxFkPYcTQ/badge)](https://hackmd.io/96BFPSiRQtK78NxFkPYcTQ) :::info * If you're reading this, you're welcome to contribute! 🎉 * *For existing pages:* * Make use of comments and ample +1s. * Edit text directly if you find inaccuracies. * In case of doubt, reach out to the page author. * *To start working in a new direction:* * Start a new page. * Link to it below (see existing links). * Tend after the pages you authored: * Follow up on page edits and comments. * Engage in discussion with those who reach out. ::: **Main author: [Giorgos Georgiadis](https://twitter.com/TheEngineer)** Pol.is is a deliberation platform where participants are called to vote (agree/disagree/pass) on a number of statements. At the same time, they are free to add their own statements for subsequent users to vote on<sup>[[1]](#ftnt-ref1)</sup>. This document aims to study the resulting poll from a graph theoretical point of view, and derive, if possible, useful analytical properties. Possible uses for this analysis are * strengthening the polling process (e.g. resistance to coordinated voting attacks), * suggesting directions of improvement, * better understanding of the computational complexity of common actions, * ... # Introduction * [Welcome](https://hackmd.io/@ThenWho/PolisGraph) # Modeling * [Definitions](https://hackmd.io/@ThenWho/Definitions) * [Graph generation model](https://hackmd.io/@ThenWho/GraphGenerationModel) # Related Literature * [Literature map](https://hackmd.io/@ThenWho/RelatedLiterature) # Experiments Code for the experiments can be found on https://github.com/ThenWho/pol-is-link-prediction [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/thenwho/pol-is-link-prediction/blob/master/) * [Link prediction](https://hackmd.io/@ThenWho/LinkPrediction) # TODO / interesting directions * [Multiplex layer distance](https://hackmd.io/@ThenWho/MultiplexLayerDistance) * [Stochastic block models](https://hackmd.io/@ThenWho/StochasticBlockModels) [[1]](#ftnt-ref1) [https://roamresearch.com/#/app/polis-methods/page/1GR4r4LX8](https://roamresearch.com/#/app/polis-methods/page/1GR4r4LX8)