How Cambridge Analytica’s Facebook targeting model really worked • Hacker News Board

Re: How Cambridge Analytica’s Facebook targeting model really worked

#111

Post by mistermann » Sat, Mar 31, 2018, 2:06 AM UTC

ikeyany wrote: post #93

MattyRad wrote: post #81

Earlier quoted context omitted.

The degree to which it influenced the election is questionable. Despite all the headlines, I haven't yet seen any convincing analysis of the impact of facebook on the election (I'm not sure how one would even go about doing so). So far it seems like it's just a convenient vehicle for people that dislike the outcome of the election to express indignation.

Don't be naive http://www.bbc.com/news/world-43476762

Can you point to the part of that article containing evidence of to what degree they affected the election?

Re: How Cambridge Analytica’s Facebook targeting model really worked

#112

Post by stochastic_monk » Sat, Mar 31, 2018, 2:07 AM UTC

alexcnwy wrote: post #106

stochastic_monk wrote: post #84

Earlier quoted context omitted.

That's only accurate in the sense that because an LSTM's hidden layer is much smaller in dimension than the data on which it is trained, there is less information in it. However, it concisely represents a manifold in a much larger dimensional space and effectively captures most of the information in it. It may be (and is) lossy, but don't underestimate the expressive power of a deep neural network.

You're throwing out buzzwords instead of addressing the response. It's dimensionality reduction. You cannot recover the original object. It's like using a shadow to reconstruct the face of the person casting the shadow. Note this has nothing to do with the expressive power of a deep neural network. You are by definition trying to throw away noisy aspects of the data and generalize a lower dimensional manifold from a…

You're right that it's really just a form of dimensionality reduction. My point was just that it's a more powerful form of dimensionality reduction than PCA or NMDS.

[Edit: and that the salient characteristics are likely contained in the model.]

Re: How Cambridge Analytica’s Facebook targeting model really worked

#113

Post by brownra04 » Sat, Mar 31, 2018, 2:08 AM UTC

majormajor wrote: post #73

frenchie14 wrote: post #59

Earlier quoted context omitted.

Outside of the tech bubble, simply saying "yes" would be disingenuous. They're not even asking the question in the first place

I think retargeting has thoroughly blown up the idea that ads online are shown to everyone. My non-technical acquaintances are very aware of why certain products follow them around the internet in ads.

But do people assume the same thing about, say, Google search results? Promoted posts on Reddit? The ads (or natural posts) on Snapchat or Instagram?

I agree that it's pretty obvious you're being retargeted when ads for camping supplies start showing up three days after you search for them on Amazon. But the practice of "personalization" of results and ads is far larger and deeper, to a degree that most people never seem to think about.

Re: How Cambridge Analytica’s Facebook targeting model really worked

#114

Post by tasty_freeze » Sat, Mar 31, 2018, 2:11 AM UTC

frozenlettuce wrote: post #66

emodendroket wrote: post #19

I am really puzzled by the Cambridge Analytica scandal. It's not particularly savory, but is there something happening here that it wasn't basically already known about how Facebook worked? By the protests of their own executive, the system was working as designed, and at worst Cambridge Analytica misled them about how they intended to use the data, right? There was no actual security breach here, as far as I can und…

It became a "problem" because it helped Trump win.

This answer ignores some known details of the story. Cambridge Analytica didn't just buy targeted ads from Facebook. They used a sockpuppet to release a fake "take a personality profile" app, which then allowed them to gather tons of data against the Facebook terms of use.

The CEO of Cambridge Analytica has also been recorded telling a (fake) potential client that they routinely blackmail people using prostitutes and who knows what else.

So unless you can show that Clinton's campaign was doing the same things, your claim is a false equivalence.

Re: How Cambridge Analytica’s Facebook targeting model really worked

#115

Post by ikeyany » Sat, Mar 31, 2018, 2:17 AM UTC

mistermann wrote: post #111

ikeyany wrote: post #93

Earlier quoted context omitted.

Don't be naive http://www.bbc.com/news/world-43476762

Can you point to the part of that article containing evidence of to what degree they affected the election?

The admission by the company executive.

Re: How Cambridge Analytica’s Facebook targeting model really worked

#116

Post by dmix » Sat, Mar 31, 2018, 2:19 AM UTC

joncp wrote: post #53

godelski wrote: post #4

> has revealed that his method worked much like the one Netflix uses to recommend movies. I'm not sure this is the model you want to emulate. The suggestions are terrible and continually getting worse.

It sure seems that way. It's almost as if Netflix is giving in to pressure from content owners (which now includes themselves) to downplay or even weaken their suggestions. First, they got rid of those wonderful ranked lists that made us love Netflix in the first place, replacing them with the much more opaque cover art carousel view. Then they started mixing in lower-ranked items into the carousel. Finally, they swi…

I've heard rumours that the internal backlash at Netflix against 5 star ratings happened with Amy Schumer's most recent comedy special which had thousands of 1 star reviews on Netflix. Which was one of their most expensive comedy productions and whose release coincided not long before the switch over to vague thumbs up/down.

Note, the comedy special was similarly panned across the press and social media as being repetitive of her previous work, extremely predictable punchlines, and when seemingly good later exposed to be highly derivative of other comedians work.

But regardless of the reality/honesty of her rating it was apparently not good for Netflix's business when they let users destroy content they produced destroy it on their own web site via user generated content.

So the suits (heavily swayes by their production studio and Hollywood) were able to convince the product team to hurt the UX for 90% in order to protect the popularity of the 10% of content they own.

The truth may be good for consumers in almost all situations. But sadly the interests of executives dealing closely with high value B2B partners and investors tend to have a way to out-valuing the interests of the average user (not to mention far out valuing power users).

So I guess we have to rely on 3rd party IMDb web extensions which inject into Netflix in order to get honest ratings.

Re: How Cambridge Analytica’s Facebook targeting model really worked

#117

Post by rmateus » Sat, Mar 31, 2018, 2:23 AM UTC

demirev wrote: post #60

alexbeloi wrote: post #31

Earlier quoted context omitted.

They used it to predict political affiliation of people that don't explicitly state a party preference. The two parties already have a list of registered party members (and they can see who on Facebook explicitly states their party preference), for those members the main goal is higher turnout (they are the training data). The other voters they're interested in are unregistered (e.g. independent) voters that are like…

Did the app really grant them continuous access to user info? I thought it was a one-off thing - they get your data at the time of use (and your friends') and that's it. Plus the approach you outlined would require the user to like/dislike things based on the add they saw, so CA can observe a change in the predicted affiliation (they didn't have access to posts as far as I know). I don't think it would have that effe…

> I suspect it was a simpler use case - they would group users into segments, and then craft different add strategies for each one (maybe based on other research or just expert opinion).

It is in this last process that it is individual-based. It is in this last process that AB tests are done individually as a function of the specific strategy applied to him/her

Re: How Cambridge Analytica’s Facebook targeting model really worked

#118

Post by vuln » Sat, Mar 31, 2018, 2:24 AM UTC

neuronexmachina wrote: post #102

vuln wrote: post #77

Earlier quoted context omitted.

This is exactly it. At least it stops the news from droning on and on about Russia. I thought Clinton spent large amounts of money on data and the Democrats admitted the data was bad or at least that was their excuse. How much did CA pay for this data? I still find it crazy that Trump campaign spent 30% of what Hillary did and still won. The Russians used 100k$ worth of ads to sway the election. This stuff doesn't t…

Do you have any sources for your claim about how the Clinton campaign acquired FB data and how they used it? Was any of it acquired fraudulently and/or in violation of FB's ToS, like CA's data was?

I said she spent money on data.

https://www.washingtonpost.com/news/post-politics/wp/2016/11...

https://www.cnn.com/2017/06/02/politics/hillary-clinton-dnc-...

Re: How Cambridge Analytica’s Facebook targeting model really worked

#119

Post by flippy2 » Sat, Mar 31, 2018, 2:26 AM UTC

pbalau wrote: post #69

etiam wrote: post #41

Spoiler warning. Article punchline ahead. "The whole point of a dimension reduction model is to mathematically represent the data in simpler form. It’s as if Cambridge Analytica took a very high-resolution photograph, resized it to be smaller, and then deleted the original. The photo still exists — and as long as Cambridge Analytica’s models exist, the data effectively does too." That's an eloquent piece of explanati…

If I tell you I like furry porn, is there a way for me to make sure you forget that? This has lots of implications, many of them placing the "blame" on me for telling you this.

That’s strangely specific....

Hmmm

Re: How Cambridge Analytica’s Facebook targeting model really worked

#120

Post by darawk » Sat, Mar 31, 2018, 2:30 AM UTC

stochastic_monk wrote: post #112

alexcnwy wrote: post #106

Earlier quoted context omitted.

You're throwing out buzzwords instead of addressing the response. It's dimensionality reduction. You cannot recover the original object. It's like using a shadow to reconstruct the face of the person casting the shadow. Note this has nothing to do with the expressive power of a deep neural network. You are by definition trying to throw away noisy aspects of the data and generalize a lower dimensional manifold from a…

You're right that it's really just a form of dimensionality reduction. My point was just that it's a more powerful form of dimensionality reduction than PCA or NMDS. [Edit: and that the salient characteristics are likely contained in the model.]

Precisely because it's more powerful, it doesn't encode the identifying information of the original data. Something like PCA likely would retain identifying characteristics (depending on how many low-rank vectors you drop).