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The Columbia Journalism Review has some analysis of the problem of disinformation and propaganda being actively spread over social control media. As the situation is studied more, albeit belatedly, the nature of social control's business model gets more daylight.
"That fundamental goal is to get the user to stay as long as possible," Ghosh said in an interview. "Their motivations are different—for platforms, it is to maximize ad space, to collect more information about the individual, and to rake in more dollars; and for the disinformation operator, the motive is the political persuasion of the individual to make a certain decision. But until we change that alignment, we are not going to solve the problem of disinformation on these platforms."
After Mueller released his indictments, sociologist Zeynep Tufekci noted on Twitter that the indictment "shows [Russia] used social media just like any other advertiser/influencer. They used the platforms as they were designed to be used."
The phrase surveillance capitalism gets more traction as it becomes acknowledged that while social control media do not actively spread disinformation and propaganda it is a side effect of collecting as much personal information as legally (and somtimes illegally) allowed. That information is aggregated from multiple sources both internal and external to social control media itself. As a result it is getting increasingly difficult to distinguish between disinformation and authentic political speech.
Automated attacks make that differentiation that much harder. Faecebook gets the most attention, but the others, including YouTube work the same way and can thus be manipulated just as easily. (Ed: Speaking of YouTube, to single out one topic as an example, as seen recently with FCC comments on Net Neutrality, only 17%of the comments the FCC received were legitimate with the rest filled in by clumsy bots.)
Source : Fake news is part of a bigger problem: automated propaganda
(Score: 3, Informative) by AthanasiusKircher on Saturday February 24 2018, @01:17AM
This is ABSOLUTELY false. And it can be statistically proven to be not only false, but a gross mischaracterization of reality.
You can "correlate" anything with anything. I could go into a database of random demographic stat A and start comparing it to random stats B, C, D, and E. I can try out subpopulations and various subsets. I can mix and match. I can likely create trillions of potential pairwise variables to compare from such a set of data. And among them, I will undoubtedly find a large number of very highly "correlated" things, according to standard statistical metrics.
There's a guy who made a blog [tylervigen.com] and a book using this very methodology.**
There are an incredibly large number of potential variables in the universe that you could start comparing to other variables. And inevitably you will find things that display a ridiculously high amount of "correlation" within random choices of datasets. And the vast majority of said correlations will be meaningless and non-causal in nature.
The unmentioned assumption in your statements is that generally when scientists or experiments start looking for correlations, they are choosing things that they feasibly think could have a correlation. That is, there's some logical connection, which would serve as the basis for causation. But the vast majority of potential pairwise variables in the universe have no such reasonable basis for connection (unless, I suppose, if you are a Jungian), and thus the vast majority of potential correlations that could exist are non-causal in nature.
The larger point here is the problems that come about in figuring out what are reasonable assumptions about possible connections. There are possible causal connections we don't tend to imagine, because we haven't seen evidence of them before. And there are "obvious" candidates for causal connections that turn out not to be so, but we can be misled by confirmation bias in data collection, analysis, and apparent "correlations." Science has the difficult task of trying to figure out the reasonable assumptions for coming up with potential causal connections and then verifying them.
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** Note: Yes, the author of that blog "cheats" by deliberately misusing statistics. He arbitrarily selects variables, time windows, etc. that show the best correlations. But if you enlarge the perspective to all potential measurements of all possible variables in the universe, it's pretty clear that you could come up with correlations much higher than any statistical metric standard for "significance" just by chance through combinations of quadrillions of variables with quadrillions of other random variables. While you may not be able to generate a formal mathematical proof, you can easily make a more informal proof that the number of meaningless spurious correlations is likely uncountably larger than the number of meaningful ones in the universe, at least to the level of precision demanded by standard casual metrics for "significance."
Bottom line is that the universe has a lot more randomness than most people are willing to acknowledge, and most times you "see a pattern" where it's unexpected, it's probably just a coincidence.