There were millions of these searches every year. A large number of Americans were, in the privacy of their own homes, making shockingly racist inquiries. The more I researched, the more disturbing the information got.
On Obama’s first election night, when most of the commentary focused on praise of Obama and acknowledgment of the historic nature of his election, roughly one in every hundred Google searches that included the word “Obama” also included “kkk” or “nigger(s).” Maybe that doesn’t sound so high, but think of the thousands of nonracist reasons to Google this young outsider with a charming family about to take over the world’s most powerful job. On election night, searches and sign-ups for Stormfront, a white nationalist site with surprisingly high popularity in the United States, were more than ten times higher than normal. In some states, there were more searches for “nigger president” than “first black president.”
There was a darkness and hatred that was hidden from the traditional sources but was quite apparent in the searches that people made.
Those searches are hard to reconcile with a society in which racism is a small factor. In 2012 I knew of Donald J. Trump mostly as a businessman and reality show performer. I had no more idea than anyone else that he would, four years later, be a serious presidential candidate. But those ugly searches are not hard to reconcile with the success of a candidate who—in his attacks on immigrants, in his angers and resentments—often played to people’s worst inclinations.
The Google searches also told us that much of what we thought about the location of racism was wrong. Surveys and conventional wisdom placed modern racism predominantly in the South and mostly among Republicans. But the places with the highest racist search rates included upstate New York, western Pennsylvania, eastern Ohio, industrial Michigan and rural Illinois, along with West Virginia, southern Louisiana, and Mississippi. The true divide, Google search data suggested, was not South versus North; it was East versus West. You don’t get this sort of thing much west of the Mississippi. And racism was not limited to Republicans. In fact, racist searches were no higher in places with a high percentage of Republicans than in places with a high percentage of Democrats. Google searches, in other words, helped draw a new map of racism in the United States—and this map looked very different from what you may have guessed. Republicans in the South may be more likely to admit to racism. But plenty of Democrats in the North have similar attitudes.
Four years later, this map would prove quite significant in explaining the political success of Trump.
In 2012, I was using this map of racism I had developed using Google searches to reevaluate exactly the role that Obama’s race played. The data was clear. In parts of the country with a high number of racist searches, Obama did substantially worse than John Kerry, the white Democratic presidential candidate, had four years earlier. The relationship was not explained by any other factor about these areas, including education levels, age, church attendance, or gun ownership. Racist searches did not predict poor performance for any other Democratic candidate. Only for Obama.
And the results implied a large effect. Obama lost roughly 4 percentage points nationwide just from explicit racism. This was far higher than might have been expected based on any surveys. Barack Obama, of course, was elected and reelected president, helped by some very favorable conditions for Democrats, but he had to overcome quite a bit more than anyone who was relying on traditional data sources—and that was just about everyone—had realized. There were enough racists to help win a primary or tip a general election in a year not so favorable to Democrats.
My study was initially rejected by five academic journals. Many of the peer reviewers, if you will forgive a little disgruntlement, said that it was impossible to believe that so many Americans harbored such vicious racism. This simply did not fit what people had been saying. Besides, Google searches seemed like such a bizarre dataset.
Now that we have witnessed the inauguration of President Donald J. Trump, my finding seems more plausible.
The more I have studied, the more I have learned that Google has lots of information that is missed by the polls that can be helpful in understanding—among many, many other subjects—an election.
There is information on who will actually turn out to vote. More than half of citizens who don’t vote tell surveys immediately before an election that they intend to, skewing our estimation of turnout, whereas Google searches for “how to vote” or “where to vote” weeks before an election can accurately predict which parts of the country are going to have a big showing at the polls.
There might even be information on who they will vote for. Can we really predict which candidate people will vote for just based on what they search? Clearly, we can’t just study which candidates are searched for most frequently. Many people search for a candidate because they love him. A similar number of people search for a candidate because they hate him. That said, Stuart Gabriel, a professor of finance at the University of California, Los Angeles, and I have found a surprising clue about which way people are planning to vote. A large percentage of election-related searches contain queries with both candidates’ names. During the 2016 election between Trump and Hillary Clinton, some people searched for “Trump Clinton polls.” Others looked for highlights from the “Clinton Trump debate.” In fact, 12 percent of search queries with “Trump” also included the word “Clinton.” More than one-quarter of search queries with “Clinton” also included the word “Trump.”
We have found that these seemingly neutral searches may actually give us some clues to which candidate a person supports.
How? The order in which the candidates appear. Our research suggests that a person is significantly more likely to put the candidate they support first in a search that includes both candidates’ names.
In the previous three elections, the candidate who appeared first in more searches received the most votes. More interesting, the order the candidates were searched was predictive of which way a particular state would go.