Daily Productive Sharing 800 - Twitter Community Notes
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Vitalik Buterin analyzed Community Notes by Twitter:
- Community Notes are neither written nor curated by central experts. Instead, they can be created, rated, and voted on by anyone who meets certain criteria, and their selection is governed by an open-source algorithm.
- Any Twitter user who meets specific criteria can participate in Community Notes. They can rate existing notes and eventually write their own. The ratings are given on a 3-point scale of helpfulness.
- The notes are prioritized by an algorithm that values positive ratings from a diverse range of perspectives. It utilizes a standard machine learning model to predict the values and is not hardcoded to specific political orientations.
- The underlying code for this feature is complex, comprising 6282 lines across 22 files. But the algorithm aims to be simple and reasonably easy to analyze, with clear mathematical properties showing its optimal functionality.
- Although only a small percentage of misleading tweets may receive a contextual note, Community Notes still serves as a valuable educational tool. Its goal is not to correct every misleading statement but to remind people that multiple perspectives exist and to encourage critical evaluation of information.
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Vitalik Buterin 详细分析了 Twitter 的 Community Notes 机制：
- Community Notes 并不是由专家集中制定的。相反，任何符合特定条件的人都可以创建、评分和投票，它们的选择由一个开源算法控制。
- 任何符合特定条件的 Twitter 用户都可以参与 Community Notes。他们可以对现有的笔记进行评分，并最终编写自己的笔记。评分是基于有助度的三点量表。
- 笔记的优先级由一种算法决定，该算法重视来自多样化视角的积极评分。它使用标准的机器学习模型来预测值，并且没有硬编码到特定的政治方向。
- 这个功能的底层代码相当复杂，包括22个文件的6282行。但是算法的目标是简单且合理易于分析。
- 尽管只有少量的误导性推文可能会收到 Community Notes， 但它仍然是一种有价值的工具。它的目标不是纠正每一个误导性的陈述，而是提醒人们存在多种观点，并鼓励对信息进行批判性评估。
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