Thread by @mark_ledwich

1. I worked with Anna Zaitsev (Berkely postdoc) to study YouTube recommendation radicalization. We painstakingly collected and grouped channels (768) and recommendations (23M) and found that the algo has a deradicalizing influence.

Pre-print:
arxiv.org/abs/1912.11211
🧵

2. It turns out the late 2019 algorithm
*DESTROYS* conspiracy theorists, provocateurs and white identitarians
*Helps* partisans
*Hurts* almost everyone else.

👇 compares an estimate of the recommendations presented (grey) to received (green) for each of the groups:

3. Check out recfluence.net to have a play with this new dataset. We also include categorization from @manoelribeiro et a.l. and other studies so you can see some alternative groupings.

All of the code and data is free to review to use github.com/markledwich2/Y…

4. My new article explains in detail. It takes aim at the NYT (in particular, @kevinroose) who have been on myth-filled crusade vs social media. We should start questioning the authoritative status of outlets that have soiled themselves with agendas.

medium.com/@markoledwich/…

6. Thanks 🙏 to everyone that helped: @LTF_01 @sudonhim @jmrphy @Waldo000000 and our anonymous third channel reviewer.

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