Data available for social science research is expected to increase exponentially in the coming decades, along with new tools and procedures to analyze them. These new big data resources present many opportunities for social scientists but also pose significant challenges. Big data allow researchers to observe actual behavior rather than relying on self-reported information – providing the basis for real-time, data-based decision-making. However, big data can also suffer from problems such as respondent recall bias, reporting error, and data entry error. In the social sciences, big data can be used to monitor public opinion, track emerging health issues, analyze social networks, and develop models to help predict crime and other behaviors. Big data also provide opportunities to reach hard-to-reach populations – those who may be reluctant to respond to surveys but who use social media on a regular basis. Statisticians and social scientists can help infuse appropriate methods into the process of analyzing big data to ensure that conclusions are not overstated. Effective research will require collaboration with researchers in other disciplines, including computer scientists, to create a new generation of “computational social scientists” who can effectively use big data to answer questions about human behavior and forecast change.