Finally, I was waiting for someone to talk about the model itself. It makes sense that SVD or something like it (PCA, co-occurrence, etc) would be used.
But I also wonder what exactly you are going to do with the predictions. What exactly do you show to someone to make them more likely to go and vote if they are inclined to vote your way, or make them stay at home otherwise? Is there evidence that whatever you're showing actually works? Or do you try to change people's minds? What do you do?
Knowing how the state of things -in this case, people's voting inclinations- is not the same as knowing what to do, ie a strategy.
I don't know how effective it is, I'd like to learn more. But I smell the possibility that these CA type firms are simply selling snakeoil to desperate political activists.
One example I can provide is of gun control topics.
If you understand someone's mentality on the subject you can decide if they see:
1) An ad with someone breaking into a home and the homeowner defending themselves with a firearm (sell insurance?)
2) A grandfather and grandson on a hunting trip (hunting supplies?)
3) Or maybe gun violence hotline with powerful images.
The people seeing these ads are under the assumption that everyone else sees them, not that it's specifically targeted at their personality type. These affect if you think other people understand your issue or not.
Thus affecting your motivation and attitude.
If you see an ad that fits your mindset, you think you're on the majority side. This was powerful in classic media, it's just as powerful now.
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.
Agreed. Although we all hate it, if my mom searches for hard sided luggage on amazon and ads for it follow her to all manner of other sites - that’s the best way for non-tech types to get some of the idea here.
The truth is WAY worse of course, but she immediately knows the ads she saw won’t show for me as well.
There's an occasional thing in UK politics where some public figure X has a go at another figure Y for having offensive ads on their website, without realising about the targeting which means the ads are driven by their own search results.
I think most people do assume the same with search results. How many do you think assume that the ads on the TV they see could be different than what the neighbor is seeing when watching the same channel with the same cable company?
I think a lot of people assume that others see the same news and the way people act you'd think they assume that others see the same things in their newsfeed/timeline / facebook thing - and wonder how others could have a different view.
Even when I explain how ads can be different, I don't think people really want to believe it, or understand it, and they certainly do not realize the power of these targeting abilities..
Before Netflix stopped showing the number of stars next to content, I used to sort of depend on it for choosing a movie. In fact, I sort of miss it now, and spend more time sifting through content undecided. That's because I am clueless about movies. I believe that there are people who are as unsure about electoral candidates (as in, at a given day, they don't favor one candidate above others) as I am about choosing movies. When push comes to shove (my wife's irritation quotient above threshold) in terms of making a decision, an advertisement that someone saw couple of days back can definitely assist in making a choice at the split second.
> I don't know how effective it is, I'd like to learn more. But I smell the possibility that these CA type firms are simply selling snakeoil to desperate political activists.
According to the article:
"The accuracy he claims suggests it works about as well as established voter-targeting methods based on demographics like race, age, and gender....the digital modeling Cambridge Analytica used was hardly the virtual crystal ball a few have claimed."
It's pretty clear that they were selling snakeoil. In fact, the use of CA wasn't particularly helpful to anyone [1]...hiring them was just a prerequisite for obtaining campaign contributions from the Mercer family, who had put up the money behind CA [2].
It is reasonable to assume that a marketing message written with the profile of the targeted person in mind works better than generic message.
In Facebook campaigns you can use certain things, such as user's interest, to select who sees your message.
I'm not an expert on Facebook analytics, but I believe you can get pretty good stats on how your campaigns are working, how much promoted posts get shared etc.
This sounds like the holy grail for advertising. You get to write your message for certain profile and get quick feedback how it worked. Even if the system is not perfect, you would have an advantage compared to somebody else who is spending the same amount of money and not using similar targeting.
Maybe their model also allowed them to find social influencers with many followers. Being able to targer these people and get them to share your message would be really good.
The article compares this to the effectiveness of traditional voter targeting methods. I'm not sure what the parameters used on those are, but maybe all of them are not available on FB, justifying the need for something else.
> What exactly do you show to someone to make them more likely to go and vote if they are inclined to vote your way, or make them stay at home otherwise?
Geography, at a first pass, over multiple elections. This is how TV testing works. Pick "similar" geographies and run your marketing in one. If the effect is large enough, it pops out. Not quite a diff-in-diff, but a start.
Or don't look at votes, look at candidate likes and shares over time, especially as they shift.
The defined metric doesn't have to be "propensity for this individual to vote for a candidate." It can be "percentage delta over untreated markets compared to prior campaigns."
Data is terrible, especially for polarizing candidates like Trump. People simply lie in public about not voting for him, afraid of backlash that they will receive.
And there's a big question mark over whether lessons learned (ie parameters) from one election are valid for the next.
What if all the sensitivities are dependent on the length of the candidates' hair? It seems the total hair length of the two candidates was a maximum at the last election. Another time you might be sampling more towards the middle.
Door to door canvassers these days carry devices that tell you what topics to bring up and what topics not to bring up at a certain address, even distinguishing between individuals at an address; some are told to demand a husband let them talk to the wife, for example.
I don't know about the specific campaigns that you are referring to, but in my experience a lot of the information used in campaigns I've been involved in comes from previous canvassing sessions. Political parties in most countries are involved at many levels where there are elections. Canvassing doesn't just take place for the big elections.
One year they will have been round and had a lengthy discussion with Mrs X, but Mr X slammed the door in their face another time. This was somewhat lower tech: the information was printed out and attached to a clipboard.
Most of the time this information is correct. It's more interesting when it's really incorrect. That said, some of the best sessions I've been involved in were where there was no information.
Exactly. This is the old-fashioned approach to campaign targetting that Cambridge Analytica was trying (and failing) to replace: just send a bunch of volunteers to talk to them about who they're voting for and why, then put that in your big database. One of the dirty not-so-secrets about CA is that according to the Trump campaign, they were abandoned completely in favour of that old-fashioned approach because they were worse. Similarly, if you've been paying attention, you might have noticed a few insider stories about how one of the Hillary Clinton campaign's big screw-ups was underestimating the importance of that data compared to modern big data tech and basically throwing a lot of it in the trash. This didn't get nearly as much coverage as the idea that Cambridge Analytica, Trump, and Facebook were conspiring to brainwash the population, probably because it was less juicy a narrative and kind of embarassing to the Clinton campaign and the DNC.
Shortly after the election, I read something saying that the actual ads were targeted soundbites at specific demographics likely to vote Democrat, run shortly before the election with the intention of suppressing voter turnout.
But I also wonder what exactly you are going to do with the predictions. What exactly do you show to someone to make them more likely to go and vote if they are inclined to vote your way, or make them stay at home otherwise? Is there evidence that whatever you're showing actually works? Or do you try to change people's minds? What do you do?
Knowing how the state of things -in this case, people's voting inclinations- is not the same as knowing what to do, ie a strategy.
I don't know how effective it is, I'd like to learn more. But I smell the possibility that these CA type firms are simply selling snakeoil to desperate political activists.