Wednesday, April 11, 2018

So do we know whether targeted fake news helped swing the election to Donald Trump?


scientificamerican |  When I was a teenager, my parents often asked me to come along to the store to help carry groceries. One day, as I was waiting patiently at the check-out, my mother reached for her brand new customer loyalty card. Out of curiosity, I asked the cashier what information they record. He replied that it helps them keep track of what we’re buying so that they can make tailored product recommendations. None of us knew about this. I wondered whether mining through millions of customer purchases could reveal hidden consumer preferences and it wasn’t long before the implications dawned on me: are they mailing us targeted ads?

This was almost two decades ago. I suppose the question most of us are worried about today is not all that different: how effective are micro-targeted messages? Can psychological “big data” be leveraged to make you buy products? Or, even more concerning, can such techniques be weaponized to influence the course of history, such as the outcomes of elections? On one hand, we’re faced with daily news from insiders attesting to the danger and effectiveness of micro-targeted messages based on unique “psychographic” profiles of millions of registered voters. On the other hand, academic writers, such as Brendan Nyhan, warn that the political power of targeted online ads and Russian bots are widely overblown.

In an attempt to take stock of what psychological science has to say about this, I think it is key to disentangle two prominent misunderstandings that cloud this debate.

First, we need to distinguish attempts to manipulate and influence public opinion, from actual voter persuasion. Repeatedly targeting people with misinformation that is designed to appeal to their political biases may well influence public attitudes, cause moral outrage, and drive partisans further apart, especially when we’re given the false impression that everyone else in our social network is espousing the same opinion. But to what extent do these attempts to influence translate into concrete votes? 

The truth is, we don’t know exactly (yet). But let’s evaluate what we do know. Classic prediction models that only contain socio-demographic data (e.g. a person’s age), aren’t very informative on their own in predicting behavior. However, piecing together various bits of demographic, behavioral, and psychological data from people, such as pages you’ve liked on Facebook, results from a personality quiz you may have taken, as well as your profile photo (which reveals information about your gender and ethnicity) can improve data quality. For example, in a prominent study with 58,000 volunteers, a Stanford researcher found that a model using Facebook likes (170 likes on average), predicted a whole range of factors, such as your gender, political affiliation, and sexual orientation with impressive accuracy.

In a follow-up study, researchers showed that such digital footprints can in fact be leveraged for mass persuasion. Across three studies with over 3.5 million people, they found that psychologically tailored advertising, i.e. matching the content of a persuasive message to an individuals’ broad psychographic profile, resulted in 40% more clicks and in 50% more online purchases than mismatched or unpersonalized messages. This is not entirely new to psychologists: we have long known that tailored communications are more persuasive than a one-size-fits all approach. Yet, the effectiveness of large-scale digital persuasion can vary greatly and is sensitive to context. After all, online shopping is not the same thing as voting!

So do we know whether targeted fake news helped swing the election to Donald Trump?

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