Core Concepts: Computational social science.

Cell phone tower data predicts which parts of London can expect a spike in crime (1). Google searches for polling place information on the day of an election reveal the consequences of different voter registration laws (2). Mathematical models explain how interactions among financial investors produce better yields, and even how they generate economic bubbles (3). These are just a few examples of how a suite of technologies is helping bring sociology, political science, and economics into the digital age. Such social science fields have historically relied on interviews and survey data, as well as censuses and other government databases, to answer important questions about human behavior. These tools often produce results based on individuals—showing, for example, that a wealthy, well-educated, white person is statistically more likely to vote (4)—but struggle to deal with complex situations involving the interactions of many different people. A growing field called “computational social science” is now using digital tools to analyze the rich and interactive lives we lead. The discipline uses powerful computer simulations of networks, data collected from cell phones and online social networks, and online experiments involving hundreds of thousands of individuals to answer questions that were previously impossible to investigate. Humans are fundamentally social creatures and these new tools and huge datasets are giving social scientists insights into exactly how connections among people create societal trends or heretofore undetected patterns, related to everything from crime to economic fortunes to political persuasions. Although the field provides powerful ways to study the world, it’s an ongoing challenge to ensure