Et firma bruger Big Data til at påvirke stemmer.
er fra Motherboard.vice.com, som virker troværdig. Der står bl.a. at demokraterne i USA har gjort nogenlunde det samme som Trump, men at de ikke var så avancerede og brugte ikke psychometric eller psykografisk profilering.
Desuden læste jeg på en troværdig, dansk side, kommunikationsforum.dk
, det samme:" Datadrevet psykografisk segmentering vandt valget i USA / Brexit for både Trump og Brexit-bevægelsen. Analysefirmaet bag var Cambridge Analytica."
Her et kort referat på dansk:
Et firma køber data om amerikanere. Alle disse data om personer fortæller også personens adresse.
Med en algoritme kan firmaet udregne, hvordan personer i et hus på en adresse er.
Trumps kampagnefolk kunne gå til et hus og på en app på deres mobil se om der var personer i huset, som kunne overtales til at stemme på Trump og hvilke udsagn som kunne overbevise dem.
På facebook er der annoncer, som er helt målrettet personen. Måske kunne det firma, som Trump anvendte, målrette annoncer, som var udformet efter personernes profil, så de stemte på Trump, eller hvis de var demokrater ikke gik hen og stemte.
Uddrag fra artiklen
Political observers had indeed noticed some striking similarities between Trump’s agenda and that of the right-wing Brexit movement. But few had noticed the connection with Trump’s recent hiring of a marketing company named Cambridge Analytica.
“Pretty much every message that Trump put out was data-driven," says Cambridge Analytica CEO Alexander Nix.
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.
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.
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.
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.
The fact that Trump spent so little money may also be explained by the effectiveness of personality-based advertising.