What were the "very dishonest" statements?
IIRC they also started off saying it was all algorithmic.
Their investigation found "no evidence of systematic political bias." So, not sure where the very dishonest statement is here.
I think the point is that a casual observer would not have guessed trending tropics were so influenced by human intervention, and might have taken them to be an actual reflection of the Facebook hivemind. Further the statement of "no evidence of systematic political bias" is a bit hard to swallow given reports of Facebook employees asking "what Facebook can do to stop Donald Trump" at their all-hands (one of the top 5 questions in a poll [0] not just a lone employee walking up to the microphone). Further, the people curating these feeds are probably underpaid and young, and hence are probably going to skew left of the average journalist. Bias doesn't have to be explicit to be systematic.
Anyway I find Donald Trump + much of the rest of the GOP field pretty reprehensible politics-wise, Facebook seems to be handling things well [1], and we shouldn't worry about a conflict of interest as much as w/ advertising+privacy [2], but some amount of vigilance seems wise given how much influence these platforms can have over political outcomes [3]. Twitter in particular seems to have made a few fairly illiberal moves lately from my POV.
[0] http://gizmodo.com/facebook-employees-asked-mark-zuckerberg-...
[1] https://medium.com/@glennbeck/what-disturbed-me-about-the-fa...
[2] One shouldn't discount the H1B angle completely though.
[3] http://www.politico.com/magazine/story/2015/08/how-google-co...
One was shut down almost immediately, one was still up when the video was posted.
Won't name them as I don't want to drag politics into HN but I am fairly convinced it is repeatable (and if anyone is interested in giving it a try I can try to dig out a reference and post.)
If moderation is done by humans, you could simply prove that one moderator had a worse morning than the other, or that through luck of the draw Group A went to a sympathetic moderator while group B did not. That could demonstrate individual bias, but not institutional.
If moderation is automated, how do you control for the weight of keywords, phrases, etc? Maybe Group A was full of statements that almost threw a flag but not quite, while Group B contained mostly innocuous wording but (only) one phrase that actually got flagged.
If both groups were designed to be unpleasant, but various "blacklist" words and phrases are weighted differently, Group A might have achieved "flagged" weight while group Group B was "flagged -1." One might have scored 99 pts vs 100 for the other, but the visible difference is that one remains visible while the other does not.
Thinking out loud, now... let's say that Facebook does have a political bias. How do you prove that Facebook's financial success is despite that political bias, and not because of it?
Is it possible to have a monopoly on digital socialization? If you can't declare Facebook a monopoly, and therefore subject to greater regulation, then your only lever over Facebook is social pressure, presumably in the form of bad press and boycotts, which will reduce their advertising revenue. How do you prove that the existing political bias is leading them to sub-optimal revenues?
Couple of months since I saw this, so can't say for sure but I think a major point of the experiment was that the two "hate groups" were equal except which ethnic group they were directed at.