Text Analysis Can Predict Your Politics

Text Analysis Can Predict Your Politics

Text Analysis Can Predict Your Politics
Pretend for a moment that you had a pen pal overseas and they asked you to describe yourself. What would you tell them? What makes you “you”?

It turns out that which traits, characteristics and aspects of your identity you choose to focus on may say more than you realize.

For instance, they can be used to predict whether you are a Democrat or a Republican.

With the U.S. presidential race underway in earnest, I thought it would be interesting to explore what if any patterns in the way people describe themselves could be used to identify their political affiliation.

So we posed the question above verbatim to a nationally representative sample of just over n=1000 (sourced via CriticalMix) and ran the responses through OdinText.

Not surprisingly, responses to this open-ended question were as varied as the people who provided them, but OdinText was nevertheless able to identify several striking and statistically significant differences between the way Republicans and Democrats described themselves.

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Let me emphasize that this exercise had nothing to do with demographics. We’re all aware of the statistical demographic differences between Republicans and Democrats.

For our purposes, what if any specific demographic information people shared in describing themselves was only pertinent to the extent that it constituted a broader response pattern that could predict political affiliation.

For example, we found that Republicans were significantly more likely than Democrats to say they have blonde hair.

Of course, this does not necessarily mean that someone with blonde hair is significantly more likely to be a Republican; rather, it simply means that if you have blonde hair, you are significantly more likely to feel it noteworthy to mention it when describing yourself if you are a Republican than if you are a Democrat.

OdinText’s analysis turned up several predictors predictors for party affiliation, here are 15 examples indexed below.

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