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| <meta name="twitter:card" content="summary"/> | ||
| <meta name="twitter:title" content="Resources"/> | ||
| <meta name="twitter:description" content="This is a curated list of links to resources on the Internet we found helpful along the way. | ||
| Education and Theory Entropy (for data science) Clearly Explained!!! (StatQuest) Youtube video explaining surprisal and entropy."/> | ||
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| <title>Resources - Social Protocols</title> | ||
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| Social Protocols | ||
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| <li><a href="/">Home</a></li> | ||
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| <li><a href="/resources/">Resources</a></li> | ||
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| <h1 class="article-title">Resources</h1> | ||
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| <div class="article-content"> | ||
| <p><em>This is a curated list of links to resources on the Internet we found helpful along the way.</em></p> | ||
| <h2 id="education-and-theory">Education and Theory</h2> | ||
| <p><strong>Entropy (for data science) Clearly Explained!!!</strong> <em>(StatQuest)</em> Youtube video explaining surprisal and entropy. <a href="https://www.youtube.com/watch?v=YtebGVx-Fxw">[Link]</a></p> | ||
| <p><strong>Information content</strong> <em>(Wikipedia)</em> Article on surprisal (= information content). Well-written and provides some useful intuitions. <a href="https://en.wikipedia.org/wiki/Information_content">[Link]</a></p> | ||
| <p><strong>Neural Networks: Zero to Hero</strong> <em>(Andrej Karpathy)</em> Course on neural networks. <a href="https://karpathy.ai/zero-to-hero.html">[Link]</a></p> | ||
| <p><strong>Probability Monad</strong> <em>(github/jliszka)</em> Scala library to play around with probability distributions. Especially interesting to explore the implementation of a distribution as a monad. <a href="https://github.com/jliszka/probability-monad">[Link]</a></p> | ||
| <p><strong>Bayesian Networks and Causality</strong> <em>(Jason Liszka)</em> Great to get a good understanding of the concept of causality in probability theory. <a href="https://blog.jliszka.org/2013/12/18/bayesian-networks-and-causality.html">[Link]</a></p> | ||
| <p><strong>How Hacker News ranking really works: scoring, controversy, and penalties</strong> <em>(Ken Shirriff)</em> Explanation of the Hacker News ranking algorithm. Still relevant, even though the article is old. <a href="https://www.righto.com/2013/11/how-hacker-news-ranking-really-works.html">[Link]</a></p> | ||
| <p><strong>How Not To Sort By Average Rating</strong> <em>(Evan Miller)</em> Famous article about the pitfalls of ranking elements with ratings. <a href="https://www.evanmiller.org/how-not-to-sort-by-average-rating.html">[Link]</a></p> | ||
| <p><strong>Bayesian Average Ratings</strong> <em>(Evan Miller)</em> Article on how to use Bayesian averaging to sort by ratings. <a href="https://www.evanmiller.org/bayesian-average-ratings.html">[Link]</a></p> | ||
| <p><strong>Causality for Machine Learning</strong> Free course discussing causality in the context of machine learning. <a href="https://ff13.fastforwardlabs.com/">[Link]</a></p> | ||
| <p><strong>A frequentist approach to probability</strong> <em>(Jason Liszka)</em> Walk-through on building a probability monad from scratch. Very good to build intuitions around probability. Provocative reading if you think in a Bayesian way. <a href="https://blog.jliszka.org/2013/08/12/a-frequentist-approach-to-probability.html">[Link]</a></p> | ||
| <p><strong>Polis Knowledge Base</strong> List of explanations and resources provided by pol.is. Note that many links don’t seem to work anymore, but there are still many useful ones. <a href="https://compdemocracy.org/knowledge-base/">[Link]</a></p> | ||
| <p><strong>Network Science</strong> <em>(Albert-Laszló Barabási)</em> Free course on network science. <a href="http://networksciencebook.com/">[Link]</a></p> | ||
| <p><strong>Emergence of Scaling in Random Networks</strong> <em>(Albert-Laszló Barabási and Réka Albert)</em> Famous paper on a random network model with preferential attachment. Insights on self-organization in complex networks. Short read. <a href="https://arxiv.org/abs/cond-mat/9910332">[Link]</a></p> | ||
| <p><strong>Polis: Scaling Deliberation by Mapping High Dimensional Opinion Spaces</strong> Paper on the technology behind pol.is. They use PCA and dimenionality reduction techniques to infer an opinion space informally (i.e., without explicit mapping of arguments). <a href="https://www.demdis.sk/content/files/2022/11/Polis-manusript.pdf">[Link]</a></p> | ||
| <p><strong>Bridging-Based Ranking</strong> <em>(Aviv Ovadya)</em> Explanations and background on bridging-based ranking. <a href="https://www.belfercenter.org/publication/bridging-based-ranking">[Link]</a></p> | ||
| <p><strong>Bridging Systems</strong> Resources on bridging-based ranking. Links to a paper with an in-depth explanation and discussion of briding-based ranking. <a href="https://bridging.systems/">[Link]</a></p> | ||
| <p><strong>Understanding Bridge-Based Ranking</strong> <em>(Jonathan Warden)</em> Explanation of the bridging-based ranking algorithm. <a href="https://jonathanwarden.com/understanding-bridge-based-ranking/">[Link]</a> <a href="https://news.ycombinator.com/item?id=38939660">[Hacker News discussion]</a></p> | ||
| <p><strong>What do I think about Community Notes?</strong> <em>(Vitalik Buterin)</em> Explanation on and opinions about Community Notes. <a href="https://vitalik.eth.limo/general/2023/08/16/communitynotes.html">[Link]</a></p> | ||
| <p><strong>‘Generative CI’ through Collective Response Systems</strong> <em>(Aviv Ovadya)</em> Working paper on collective response systems and how they could enable “Generative Collective Intelligence”. <a href="https://arxiv.org/abs/2302.00672">[Link]</a></p> | ||
| <p><strong>Distributed Bayesian Reasoning Introduction</strong> <em>(Jonathan Warden)</em> Discussion of how Bayesian reasoning could work on a collective level to achieve collective intelligence. <a href="https://jonathanwarden.com/distributed-bayesian-reasoning-introduction/">[Link]</a></p> | ||
| <h2 id="articles">Articles</h2> | ||
| <p><strong>Social Protocols</strong> <em>(Joseph M. Reagle Jr.)</em> First use of the term “social protocol” that we know of (mid to late 90s). <a href="https://www.w3.org/Talks/980922-MIT6805/SocialProtocols.html">[Link]</a></p> | ||
| <p><strong>Collective Intelligence Design Challenges</strong> <em>(Canonical Debate Lab, CDL)</em> Write-up on collecive intelligence systems. <a href="https://canonicaldebatelab.com/cidesign/">[Link]</a></p> | ||
| <p><strong>How to hack Hacker News (and consistently hit the front page)</strong> Interesting write-up on how someone tried gaming the Hacker News algorithm. Exemplifies the kind of thinking you need to understand incentives in algorithmic content curation. <a href="https://www.indiehackers.com/post/how-to-hack-hacker-news-and-consistently-hit-the-front-page-56b4a04e12">[Link]</a></p> | ||
| <p><strong>The Quiet Death of Ello’s Big Dreams</strong> Cautionary tale about the decline of Ello, a social network for creatives. <a href="https://waxy.org/2024/01/the-quiet-death-of-ellos-big-dreams/">[Link]</a> <a href="https://news.ycombinator.com/item?id=39043871">[Hacker News discussion]</a></p> | ||
| <p><strong>Why Twitter was right to replace stars with hearts, and why you hate it</strong> <em>(Joscha Bach)</em> Tongue-in-cheek discussion of Twitter’s replacement of stars by hearts. Interesting to think about semantics of buttons. Discussion of global brain vision at the end. <a href="http://bach.ai/twitter-replaces-stars-with-hearts/">[Link]</a></p> | ||
| <h2 id="talks">Talks</h2> | ||
| <p><strong>Simple Made Easy (video)</strong> <em>(Rich Hickey)</em> Talk on how and why to build simple systems. <a href="https://www.youtube.com/watch?v=LKtk3HCgTa8">[Link]</a></p> | ||
| <h2 id="other-projects">Other Projects</h2> | ||
| <p><strong>Community Notes Guide</strong> Introductory articles on X’s community notes (formerly known as Birdwatch). <a href="https://communitynotes.twitter.com/guide/en/about/introduction">[Link]</a></p> | ||
| <p><strong>News Minimalist</strong> Filter large amounts of news articles for the most relevant ones. Uses an LLM-powered relevance score. <a href="https://www.newsminimalist.com/">[Link]</a></p> | ||
| <p><strong>Twitter’s Recommendation Algorithm</strong> High-level overview of X’s recommendation algorithm. <a href="https://blog.twitter.com/engineering/en_us/topics/open-source/2023/twitter-recommendation-algorithm">[Link]</a> <a href="https://news.ycombinator.com/item?id=35391433">[Hacker News discussion]</a></p> | ||
| <p><strong>Metaculus</strong> Crowd-sourcing forecasts on real events. <a href="https://www.metaculus.com/">[Link]</a> <a href="https://news.ycombinator.com/item?id=36740385">[Hacker News discussion]</a></p> | ||
| <p><strong>Pol.is</strong> Mapping debates with an informal argument model. Focus groups at scale. Has been used in digital democracy experiments in Taiwan. <a href="https://pol.is/home">[Link]</a></p> | ||
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| <a href='' type="application/rss+xml" target="_blank">RSS</a> | ||
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| <li><a href="https://github.com/social-protocols">GitHub</a></li> | ||
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| <li><a href="https://mas.to/@SocialProtocols">Mastodon</a></li> | ||
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| <li><a href="https://medium.com/@socialprotocols">Medium</a></li> | ||
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| <li><a href="https://socialprotocols.substack.com">Substack</a></li> | ||
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| <li><a href="https://twitter.com/socialprotocols">Twitter</a></li> | ||
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