As far as I can tell, the only way Twitter has substantively changed over the past few years is that a small (but non-trivial) number of politically obsessed left-wingers have voluntarily self-exited. Everything else is narrative.
Every social media site is like this now. They fear the scrapers. Most of the people complaining about having to log in on X, they intentionally have no account in the first place because they don't like the site's owner or something.
I say this as part of the exception. The only reason I don't use X is because they banned me for no reason. Probably not the common case.
That's what some motivated cable news researchers decided to abuse statistics to say. To be generous, I would say the article makes a significantly stronger causal claim than the experiment supports. The best description is a good exploratory algorithm audit with weak statistical and causal inference.
The analysis rests on just nine synthetic accounts, treats thousands of highly correlated feed impressions as if they provide robust independent evidence, lacks a proper baseline for the political content available on X, and reports no meaningful uncertainty, significance testing or adequately powered replication.
As far as I can tell, the only way Twitter has substantively changed over the past few years is that a small (but non-trivial) number of politically obsessed left-wingers have voluntarily self-exited. Everything else is narrative.
It's also become a whole lot more hostile to anonymous visitors, hence the topic under discussion. That's not just narrative but a fact.
Every social media site is like this now. They fear the scrapers. Most of the people complaining about having to log in on X, they intentionally have no account in the first place because they don't like the site's owner or something.
I say this as part of the exception. The only reason I don't use X is because they banned me for no reason. Probably not the common case.
That's not what the data says: https://news.sky.com/story/the-x-effect-how-elon-musk-is-boo...
That's what some motivated cable news researchers decided to abuse statistics to say. To be generous, I would say the article makes a significantly stronger causal claim than the experiment supports. The best description is a good exploratory algorithm audit with weak statistical and causal inference.
The analysis rests on just nine synthetic accounts, treats thousands of highly correlated feed impressions as if they provide robust independent evidence, lacks a proper baseline for the political content available on X, and reports no meaningful uncertainty, significance testing or adequately powered replication.