> This series of comments paints a picture of somebody starting from ideological priors and then trying to bend reality to arrive at their premade conclusion.

The irony is palpable.

> I trust actual statistics experts

I listed the issues, but if you need an expert to explain them to you in detail, then perhaps you have neither the statistical nor media literacy necessary here.

1) Selection. Only 9 accounts, no interaction, short period of time. This is not a sufficiently large or realistic sample. That is also not how users interact with the product — for example, things like dwell time directly and materially impact the algorithmic weighting. They specifically avoided any measurable interactions.

2) Base rate. They did not know if the results reflected the base rate across the platform, or algorithmic bias. In other words, did X itself skew right, or did the algorithm.

3) Unreliable classification. Their own experts rated its accuracy poorly, and those are the people most ideologically aligned with the progressive political consultancy that trained the classification model in the first place.

Never mind the “propaganda” claim, which would require showing that not only was the algorithmic bias real (not demonstrated), but that the intent was propaganda instead of — for example — simply the result of maximizing for user engagement. None of which was shown.