How Big Data and ML helped Trump win

Nice article on how data from our digital footprint was used to make targeted campaigning for Trump - https://motherboard.vice.com/en_us/article/mg9vvn/how-our-likes-helped-trump-win 

The origin of approach

• The approach that Kosinski and his colleagues developed over the next few years was actually quite simple. First, they provided test subjects with a questionnaire in the form of an online quiz. From their responses, the psychologists calculated the personal Big Five values of respondents. Kosinski's team then compared the results with all sorts of other online data from the subjects: what they "liked," shared or posted on Facebook, or what gender, age, place of residence they specified, for example. This enabled the researchers to connect the dots and make correlations.

• Remarkably reliable deductions could be drawn from simple online actions. For example, men who "liked" the cosmetics brand MAC were slightly more likely to be gay; one of the best indicators for heterosexuality was "liking" Wu-Tang Clan. Followers of Lady Gaga were most probably extroverts, while those who "liked" philosophy tended to be introverts. While each piece of such information is too weak to produce a reliable prediction, when tens, hundreds, or thousands of individual data points are combined, the resulting predictions become really accurate.

•  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).

Cambridge Analytica, a UK based firm, was hired to manage Trump's campaign. This is how they took Kosinski's approach and created a similar 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.