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What we buy can be used to predict our politics, race or education
What we buy can be used to predict our politics, race or education — sometimes with more than 90 percent accuracy
"The cultural divide is real, and it’s huge. Americans live such different lives that what we buy, do or watch can be used to predict our politics, race, income, education and gender — sometimes with more than 90 percent accuracy.
It turns out that people are separated not just by gun ownership, religion and their beliefs on affirmative action — but also by English muffins, flashlights and mustard."
Here's a few additional excerpts from the article (edited for brevity):
It turns out that people are separated not just by gun ownership, religion and their beliefs on affirmative action — but also by English muffins, flashlights and mustard.
To prove it, University of Chicago economists... taught machines to guess a person’s income, political ideology, race, education and gender based on either their media habits, their consumer behavior, their social and political beliefs, and even how they spent their time. [The algorithms were trained] to detect patterns in decades of responses to three long-running surveys, tuned and filtered to be consistent over time.
To determine how accurately cultural factors predicted a person’s race, education or income tier, the duo tested their algorithms on subsets of the data that the programs had never seen. To keep it fair, they omitted variables that would have been a dead giveaway — if they were predicting whether someone was liberal or conservative, for example, they wouldn’t allow the algorithms to consider the answer to “Which political party do you support?”
Nevertheless, some results are obvious, which indirectly proves that their approach can detect tangible divides. Spending predicts gender with almost perfect accuracy, for example, because men don’t buy nearly much mascara as women do, and women buy much less aftershave/cologne than men do. But others are revelatory: White people and black people are almost as different in their spending habits as rich people and poor people are, for example.
Note: San Francisco may possibly be an exception to the mascara data.
@Ted: If you had bothered to read the article and respond to the information presented there I might have some respect for your comments. Until then, your grade of pure BS is hard to beat.
@Ted Then what have Don Draper and the entire advertising industry been working on for decades? Ad people know exactly who the demographic for particular products are and now with Facebook/Google/Twitter tracking our every move, they know more about consumer demographics than ever. I actually doubt even you really believe otherwise.
@LewisBraham- Don't you just love how they slink away into the darkness when you call their bluff? They find it really hard to get past the "this is true because I say so" routine.
Comments
It turns out that people are separated not just by gun ownership, religion and their beliefs on affirmative action — but also by English muffins, flashlights and mustard.
To prove it, University of Chicago economists... taught machines to guess a person’s income, political ideology, race, education and gender based on either their media habits, their consumer behavior, their social and political beliefs, and even how they spent their time. [The algorithms were trained] to detect patterns in decades of responses to three long-running surveys, tuned and filtered to be consistent over time.
To determine how accurately cultural factors predicted a person’s race, education or income tier, the duo tested their algorithms on subsets of the data that the programs had never seen. To keep it fair, they omitted variables that would have been a dead giveaway — if they were predicting whether someone was liberal or conservative, for example, they wouldn’t allow the algorithms to consider the answer to “Which political party do you support?”
Nevertheless, some results are obvious, which indirectly proves that their approach can detect tangible divides. Spending predicts gender with almost perfect accuracy, for example, because men don’t buy nearly much mascara as women do, and women buy much less aftershave/cologne than men do. But others are revelatory: White people and black people are almost as different in their spending habits as rich people and poor people are, for example.
Note: San Francisco may possibly be an exception to the mascara data.