Language has, of course, always been a topic of interest to social scientists. However, studying language generally required the close reading of texts, and turning huge swaths of text into data wasn’t feasible. Now, with computers and digitization, tabulating words across massive sets of documents is easy. Language has thus become subject to Big Data analysis. The links that Google utilized were composed of words. So are the Google searches that I study. Words feature frequently in this book. But language is so important to the Big Data revolution, it deserves its own section. In fact, it is being used so much now that there is an entire field devoted to it: “text as data.”
A major development in this field is Google Ngrams. A few years ago, two young biologists, Erez Aiden and Jean-Baptiste Michel, had their research assistants counting words one by one in old, dusty texts to try to find new insights on how certain usages of words spread. One day, Aiden and Michel heard about a new project by Google to digitize a large portion of the world’s books. Almost immediately, the biologists grasped that this would be a much easier way to understand the history of language.
“We realized our methods were so hopelessly obsolete,” Aiden told Discover magazine. “It was clear that you couldn’t compete with this juggernaut of digitization.” So they decided to collaborate with the search company. With the help of Google engineers, they created a service that searches through the millions of digitized books for a particular word or phrase. It then will tell researchers how frequently that word or phrase appeared in every year, from 1800 to 2010.
So what can we learn from the frequency with which words or phrases appear in books in different years? For one thing, we learn about the slow growth in popularity of sausage and the relatively recent and rapid growth in popularity of pizza.
But there are lessons far more profound than that. For instance, Google Ngrams can teach us how national identity formed. One fascinating example is presented in Aiden and Michel’s book, Uncharted.
First, a quick question. Do you think the United States is currently a united or a divided country? If you are like most people, you would say the United States is divided these days due to the high level of political polarization. You might even say the country is about as divided as it has ever been. America, after all, is now color-coded: red states are Republican; blue states are Democratic. But, in Uncharted, Aiden and Michel note one fascinating data point that reveals just how much more divided the United States once was. The data point is the language people use to talk about the country.
Note the words I used in the previous paragraph when I discussed how divided the country is. I wrote, “The United States is divided.” I referred to the United States as a singular noun. This is natural; it is proper grammar and standard usage. I am sure you didn’t even notice.
However, Americans didn’t always speak this way. In the early days of the country, Americans referred to the United States using the plural form. For example, John Adams, in his 1799 State of the Union address, referred to “the United States in their treaties with his Britanic Majesty.” If my book were written in 1800, I would have said, “The United States are divided.” This little usage difference has long been a fascination for historians, since it suggests there was a point when America stopped thinking of itself as a collection of states and started thinking of itself as one nation.
So when did this happen? Historians, Uncharted informs us, have never been sure, as there has been no systematic way to test it. But many have long suspected the cause was the Civil War. In fact, James McPherson, former president of the American Historical Association and a Pulitzer Prize winner, noted bluntly: “The war marked a transition of the United States to a singular noun.”
But it turns out McPherson was wrong. Google Ngrams gave Aiden and Michel a systematic way to check this. They could see how frequently American books used the phrase “The United States are . . .” versus “The United States is . . .” for every year in the country’s history. The transformation was more gradual and didn’t accelerate until well after the Civil War ended.
Fifteen years after the Civil War, there were still more uses of “The United States are . . .” than “The United States is . . . ,” showing the country was still divided linguistically. Military victories happen quicker than changes in mindsets.
So much for how a country unites. How do a man and woman unite? Words can help here, too.
For example, we can predict whether a man and woman will go on a second date based on how they speak on the first date.
This was shown by an interdisciplinary team of Stanford and Northwestern scientists: Daniel McFarland, Dan Jurafsky, and Craig Rawlings. They studied hundreds of heterosexual speed daters and tried to determine what predicts whether they will feel a connection and want a second date.
They first used traditional data. They asked daters for their height, weight, and hobbies and tested how these factors correlated with someone reporting a spark of romantic interest. Women, on average, prefer men who are taller and share their hobbies; men, on average, prefer women who are skinnier and share their hobbies. Nothing new there.
But the scientists also collected a new type of data. They instructed the daters to take tape recorders with them. The recordings of the dates were then digitized. The scientists were thus able to code the words used, the presence of laughter, and the tone of voice. They could test both how men and women signaled they were interested and how partners earned that interest.
So what did the linguistic data tell us? First, how a man or woman conveys that he or she is interested. One of the ways a man signals that he is attracted is obvious: he laughs at a woman’s jokes. Another is less obvious: when speaking, he limits the range of his pitch. There is research that suggests a monotone voice is often seen by women as masculine, which implies that men, perhaps subconsciously, exaggerate their masculinity when they like a woman.
The scientists found that a woman signals her interest by varying her pitch, speaking more softly, and taking shorter turns talking. There are also major clues about a woman’s interest based on the particular words she uses. A woman is unlikely to be interested when she uses hedge words and phrases such as “probably” or “I guess.”