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Again, Comcast is not an "activist group" and the study literally got awarded by the Royal Statistical Society. As a cherry on top, they do owe researchers in

by vrganj 11d ago

Again, Comcast is not an "activist group" and the study literally got awarded by the Royal Statistical Society. As a cherry on top, they do owe researchers in the EU (though this was done in the UK, I know Sky has an EU presence as well) API access or similar under Article 40 of the DSA.

frumplestlatz 11d ago
https://news.ycombinator.com/item?id=49700433 https://news.ycombinator.com/item?id=49700433 https://www.allsides.com/news-source/sky-news-media-bias https://www.allsides.com/news-source/sky-news-media-bias You’re just being brazenly disingenuous at this point. The publication is left-leaning, regardless of the distant parent company. The experts they used to design and run the study were literally left-wing political advocacy groups, and a self-declared left-wing disinformation researcher. The award is an empty appeal to authority. But none of those facts matter as much as their obvious selection, base rate, and classification methodology failures.
- defrost 11d ago
  Ever so slightly left leaning by your source. Centralist and unbiased by another: https://mediabiasfactcheck.com/sky-news/ https://mediabiasfactcheck.com/sky-news/ That's quite the achievement for a group that was once firmly a propaganda wing of the global Murdoch PoV. "brazenly disingenuous" in such context is a ridiculous and emotive over statement.
  - frumplestlatz 11d ago
    > Centralist and unbiased by another It’s little odd that you replied to the least substantive fact. Disingenuous even. > "brazenly disingenuous" in such context is a ridiculous and emotive over statement. “… behavior that's not totally honest or sincere. It's disingenuous when people pretend to know less about something than they really do.” Rather like ignoring the methodology errors, or the fact that the classification model was developed by an “unapologetically progressive” political consultancy, or that their own experts rated its accuracy poorly.
- vrganj 11d ago
  You keep claiming all these statistical failures, yet you fail to produce evidence for any of them. I'm sorry, but I trust actual statistics experts more than some guy on HN that makes bold assertions with no proof. To say "nuh uh" and then not back it up with anything is below the standard of debate I expect. What are these "obvious" failures? Why have you failed to point them out concretely over several comments now? What statistical knowledge do you possess that makes them obvious to you but not to one of the most prestigious statistics organizations in the world? Please, do share with the class. Your ideological attempts to poison the well by ignoring objective data because you don't like the messenger are not an argument. To call me disengenous when you spent the last several comments failing to engage with the data and trying to hand-wave it away is ridiculous. It is getting very hard to assume good intent at this point. 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. I would be happy to be proven wrong here, but so far you have failed to do so.
  - frumplestlatz 11d ago
    > 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.

by vrganj 11d ago

frumplestlatz 11d ago

https://news.ycombinator.com/item?id=49700433 https://news.ycombinator.com/item?id=49700433 https://www.allsides.com/news-source/sky-news-media-bias https://www.allsides.com/news-source/sky-news-media-bias You’re just being brazenly disingenuous at this point. The publication is left-leaning, regardless of the distant parent company. The experts they used to design and run the study were literally left-wing political advocacy groups, and a self-declared left-wing disinformation researcher. The award is an empty appeal to authority. But none of those facts matter as much as their obvious selection, base rate, and classification methodology failures.

defrost 11d ago
Ever so slightly left leaning by your source. Centralist and unbiased by another: https://mediabiasfactcheck.com/sky-news/ https://mediabiasfactcheck.com/sky-news/ That's quite the achievement for a group that was once firmly a propaganda wing of the global Murdoch PoV. "brazenly disingenuous" in such context is a ridiculous and emotive over statement.
- frumplestlatz 11d ago
  > Centralist and unbiased by another It’s little odd that you replied to the least substantive fact. Disingenuous even. > "brazenly disingenuous" in such context is a ridiculous and emotive over statement. “… behavior that's not totally honest or sincere. It's disingenuous when people pretend to know less about something than they really do.” Rather like ignoring the methodology errors, or the fact that the classification model was developed by an “unapologetically progressive” political consultancy, or that their own experts rated its accuracy poorly.
vrganj 11d ago
You keep claiming all these statistical failures, yet you fail to produce evidence for any of them. I'm sorry, but I trust actual statistics experts more than some guy on HN that makes bold assertions with no proof. To say "nuh uh" and then not back it up with anything is below the standard of debate I expect. What are these "obvious" failures? Why have you failed to point them out concretely over several comments now? What statistical knowledge do you possess that makes them obvious to you but not to one of the most prestigious statistics organizations in the world? Please, do share with the class. Your ideological attempts to poison the well by ignoring objective data because you don't like the messenger are not an argument. To call me disengenous when you spent the last several comments failing to engage with the data and trying to hand-wave it away is ridiculous. It is getting very hard to assume good intent at this point. 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. I would be happy to be proven wrong here, but so far you have failed to do so.
- frumplestlatz 11d ago
  > 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.