Big Data, Trump & Brexit; the companies influencing elections around the globe

Saka

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read the whole thing just some highlights; i left out:
large bits about the original researcher kosinski.
how cambridge analytica the company to actually apply that research first worked with Brexit and Ted Cruz.

Anyone who has not spent the last five years living on another planet will be familiar with the term Big Data. Big Data means, in essence, that everything we do, both on and offline, leaves digital traces. Every purchase we make with our cards, every search we type into Google, every movement we make when our mobile phone is in our pocket, every "like" is stored. Especially every "like." For a long time, it was not entirely clear what use this data could have—except, perhaps, that we might find ads for high blood pressure remedies just after we've Googled "reduce blood pressure."

On November 9, it became clear that maybe much more is possible. The company behind Trump's online campaign—the same company that had worked for Leave.EU in the very early stages of its "Brexit" campaign—was a Big Data company: Cambridge Analytica.

.......

Psychometrics, sometimes also called psychographics, focuses on measuring psychological traits, such as personality. In the 1980s, two teams of psychologists developed a model that sought to assess human beings based on five personality traits, known as the "Big Five." These are: openness (how open you are to new experiences?), conscientiousness (how much of a perfectionist are you?), extroversion (how sociable are you?), agreeableness (how considerate and cooperative you are?) and neuroticism (are you easily upset?). Based on these dimensions—they are also known as OCEAN, an acronym for openness, conscientiousness, extroversion, agreeableness, neuroticism—we can make a relatively accurate assessment of the kind of person in front of us. This includes their needs and fears, and how they are likely to behave. The "Big Five" has become the standard technique of psychometrics. But for a long time, the problem with this approach was data collection, because it involved filling out a complicated, highly personal questionnaire. Then came the Internet. And Facebook. And Kosinski.

......

Kosinski and his team tirelessly refined their models. In 2012, Kosinski proved that on the basis of an average of 68 Facebook "likes" by a user, it was possible to predict their skin color (with 95 percent accuracy), their sexual orientation (88 percent accuracy), and their affiliation to the Democratic or Republican party (85 percent). But it didn't stop there. Intelligence, religious affiliation, as well as alcohol, cigarette and drug use, could all be determined. From the data it was even possible to deduce whether someone's parents were divorced.

The strength of their modeling was illustrated by how well it could predict a subject's answers. Kosinski continued to work on the models incessantly: before long, he was able to evaluate a person better than the average work colleague, merely on the basis of ten Facebook "likes." Seventy "likes" were enough to outdo what a person's friends knew, 150 what their parents knew, and 300 "likes" what their partner knew. More "likes" could even surpass what a person thought they knew about themselves. On the day that Kosinski published these findings, he received two phone calls. The threat of a lawsuit and a job offer. Both from Facebook.

.....

But it was not just about "likes" or even Facebook: Kosinski and his team could now ascribe Big Five values based purely on how many profile pictures a person has on Facebook, or how many contacts they have (a good indicator of extraversion). But we also reveal something about ourselves even when we're not online. For example, the motion sensor on our phone reveals how quickly we move and how far we travel (this correlates with emotional instability). Our smartphone, Kosinski concluded, is a vast psychological questionnaire that we are constantly filling out, both consciously and unconsciously.

.....

"So how did he do this?" Up to now, explains Nix, election campaigns have been organized based on demographic concepts. "A really ridiculous idea. The idea that all women should receive the same message because of their gender—or all African Americans because of their race." What Nix meant is that while other campaigners so far have relied on demographics, Cambridge Analytica was using psychometrics.

Nix clicks to the next slide: five different faces, each face corresponding to a personality profile. It is the Big Five or OCEAN Model. "At Cambridge," he said, "we were able to form a model to predict the personality of every single adult in the United States of America." The hall is captivated. According to Nix, the success of Cambridge Analytica's marketing is based on a combination of three elements: behavioral science using the OCEAN Model, Big Data analysis, and ad targeting. Ad targeting is personalized advertising, aligned as accurately as possible to the personality of an individual consumer.

Nix candidly explains how his company does this. First, Cambridge Analytica buys personal data from a range of different sources, like land registries, automotive data, shopping data, bonus cards, club memberships, what magazines you read, what churches you attend. Nix displays the logos of globally active data brokers like Acxiom and Experian—in the US, almost all personal data is for sale. For example, if you want to know where Jewish women live, you can simply buy this information, phone numbers included. Now Cambridge Analytica aggregates this data with the electoral rolls of the Republican party and online data and calculates a Big Five personality profile. Digital footprints suddenly become real people with fears, needs, interests, and residential addresses.

The methodology looks quite similar to the one that Michal Kosinski once developed. Cambridge Analytica also uses, Nix told us, "surveys on social media" and Facebook data. And the company does exactly what Kosinski warned of: "We have profiled the personality of every adult in the United States of America—220 million people," Nix boasts.

Nix narrows down the criteria: "Republicans"—the blue dots disappear; "not yet convinced"—more dots disappear; "male", and so on. Finally, only one name remains, including age, address, interests, personality and political inclination. How does Cambridge Analytica now target this person with an appropriate political message?

Nix shows how psychographically categorized voters can be differently addressed, based on the example of gun rights, the 2nd Amendment: "For a highly neurotic and conscientious audience the threat of a burglary—and the insurance policy of a gun." An image on the left shows the hand of an intruder smashing a window. The right side shows a man and a child standing in a field at sunset, both holding guns, clearly shooting ducks: "Conversely, for a closed and agreeable audience. People who care about tradition, and habits, and family."

OG Link: The Data That Turned the World Upside Down - Motherboard
 
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Saka

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How to keep Clinton voters away from the ballot box

Trump's striking inconsistencies, his much-criticized fickleness, and the resulting array of contradictory messages, suddenly turned out to be his great asset: a different message for every voter. The notion that Trump acted like a perfectly opportunistic algorithm following audience reactions is something the mathematician Cathy O'Neil observed in August 2016.

"Pretty much every message that Trump put out was data-driven," Alexander Nix remembers. On the day of the third presidential debate between Trump and Clinton, Trump's team tested 175,000 different ad variations for his arguments, in order to find the right versions above all via Facebook.
The messages differed for the most part only in microscopic details, in order to target the recipients in the optimal psychological way: different headings, colors, captions, with a photo or video. This fine-tuning reaches all the way down to the smallest groups, Nix explained in an interview with us. "We can address villages or apartment blocks in a targeted way. Even individuals."

In the Miami district of Little Haiti, for instance, Trump's campaign provided inhabitants with news about the failure of the Clinton Foundation following the earthquake in Haiti, in order to keep them from voting for Hillary Clinton. This was one of the goals: to keep potential Clinton voters (which include wavering left-wingers, African-Americans, and young women) away from the ballot box, to "suppress" their vote, as one senior campaign official told Bloomberg in the weeks before the election. These "dark posts"—sponsored news-feed-style ads in Facebook timelines that can only be seen by users with specific profiles—included videos aimed at African-Americans in which Hillary Clinton refers to black men as predators, for example.

Nix finishes his lecture at the Concordia Summit by stating that traditional blanket advertising is dead. "My children will certainly never, ever understand this concept of mass communication." And before leaving the stage, he announced that since Cruz had left the race, the company was helping one of the remaining presidential candidates.

Just how precisely the American population was being targeted by Trump's digital troops at that moment was not visible, because they attacked less on mainstream TV and more with personalized messages on social media or digital TV. And while the Clinton team thought it was in the lead, based on demographic projections, Bloomberg journalist Sasha Issenberg was surprised to note on a visit to San Antonio—where Trump's digital campaign was based—that a "second headquarters" was being created. The embedded Cambridge Analytica team, apparently only a dozen people, received $100,000 from Trump in July, $250,000 in August, and $5 million in September. According to Nix, the company earned over $15 million overall. (The company is incorporated in the US, where laws regarding the release of personal data are more lax than in European Union countries. Whereas European privacy laws require a person to "opt in" to a release of data, those in the US permit data to be released unless a user "opts out.")

The measures were radical: From July 2016, Trump's canvassers were provided with an app with which they could identify the political views and personality types of the inhabitants of a house. It was the same app provider used by Brexit campaigners. Trump's people only rang at the doors of houses that the app rated as receptive to his messages. The canvassers came prepared with guidelines for conversations tailored to the personality type of the resident. In turn, the canvassers fed the reactions into the app, and the new data flowed back to the dashboards of the Trump campaign.

Again, this is nothing new. The Democrats did similar things, but there is no evidence that they relied on psychometric profiling. Cambridge Analytica, however, divided the US population into 32 personality types, and focused on just 17 states. And just as Kosinski had established that men who like MAC cosmetics are slightly more likely to be gay, the company discovered that a preference for cars made in the US was a great indication of a potential Trump voter. Among other things, these findings now showed Trump which messages worked best and where. The decision to focus on Michigan and Wisconsin in the final weeks of the campaign was made on the basis of data analysis. The candidate became the instrument for implementing a big data model.

What's Next?

Another big winner is Cambridge Analytica. Its board member Steve Bannon, former executive chair of the right-wing online newspaper Breitbart News, has been appointed as Donald Trump's senior counselor and chief strategist. Whilst Cambridge Analytica is not willing to comment on alleged ongoing talks with UK Prime Minister Theresa May, Alexander Nix claims that he is building up his client base worldwide, and that he has received inquiries from Switzerland, Germany, and Australia. His company is currently touring European conferences showcasing their success in the United States. This year three core countries of the EU are facing elections with resurgent populist parties: France, Holland and Germany. The electoral successes come at an opportune time, as the company is readying for a push into commercial advertising.
 
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BocaRear

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this shyt is frightening :merchant:

we're in a new era of propaganda
 

scarhead

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This shyt is evil but fascinating. MVT testing isnt new but to see it really get applied on a massive scale in politics and apparently working is interesting to say the least. This shyt is evil tho. We're really just numbers to them.
 
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