Birdwatch: Crowd Wisdom and Bridging Algorithms can Inform Understanding and Reduce the Spread of Misinformation

A way to quantify this doesn't immediately come to my mind. Maybe reasonable metrics would be: 1. What % misleading/false posts are flagged 2. What % of those flagged are given meaningful context/corrections that are accurate. It seems there's circular logic of first determining truth with 1, and then maybe something to do with a "trust"/quality poll with 2. I suspect a good measurement would be very similar to the actual community notes implementation, since both of those are the goal of the system [1]. [1] https://arxiv.org/abs/2210.15723

Hmm sorry don't have anything. I recall hearing about some international research project that was used as input when creating the Twitter community notes but can't find it anymore. Interesting graphical tools exist nowadays to navigate the citation web and I guess one could try to backpropagate from this paper by Twitter employees, (Wojcik 2022):: https://arxiv.org/abs/2210.15723 Example navigation tool: https://www.connectedpapers.com/main/f983a4e27b457a502fba322...

A list of recent papers by Twitter-affiliated authors would be helpful, but as far as I can tell arxiv.org doesn't support that type of search. Here is the mentioned "Birdwatch" paper: https://arxiv.org/abs/2210.15723

Hi! Birdwatch ML Engineer here-- these context notes are from Birdwatch. They are written and rated by users, and the notes are only added as context to Tweets if they are rated highly enough by multiple raters who have tended to disagree in the past. The core algorithm is open source as well as all of the data, and there is lots of public documentation about it too: https://twitter.github.io/birdwatch/ https://twitter.com/birdwatch/status/1585794012052611076?s=2... https://arxiv.org/pdf/2210.15723.pdf

> Community notes are just opinions of random people on internet It's much more complicated than that. Here's the white paper: https://arxiv.org/abs/2210.15723

Here's the Community Notes whitepaper [1], for how it all works. Previous discussion [2]. [1] Birdwatch: Crowd Wisdom and Bridging Algorithms can Inform Understanding and Reduce the Spread of Misinformation, https://arxiv.org/abs/2210.15723 [2] https://news.ycombinator.com/item?id=33478845