This book progresses through four broad research designs: observing behavior, asking questions, running experiments, and creating mass collaboration. Each of these approaches requires a different relationship between researchers and participants, and each enables us to learn different things. That is, if we ask people questions, we can learn things that we could not learn merely by observing behavior. Likewise, if we run experiments, we could learn things that were not possible merely by observing behavior and asking questions. Finally, if we collaborate with participants, we can learn things that we could not learn by observing them, asking them questions, or enrolling them in experiments. These four approaches were all used in some form 50 years ago, and I’m confident that they will all still be used in some form 50 years from now. After devoting one chapter to each approach, including the ethical issues raised by that approach, I’ll devote a full chapter to ethics. As described in the Preface, I’m going to keep the main text of the chapters as clean as possible, and each of the chapters will conclude with a section called “What to read next” that includes important bibliographic information and pointers to more detailed material.
Looking ahead, in chapter 2 (“Observing behavior”), I’ll describe what and how researchers can learn from observing people’s behavior. In particular, I’ll focus on big data sources created by companies and governments. Abstracting away from the details of any specific source, I’ll describe 10 common features of the big data sources and how these impact researchers’ ability to use these data sources for research. Then, I’ll illustrate three research strategies that can be used to successfully learn from big data sources.
In chapter 3 (“Asking questions”), I’ll begin by showing what researchers can learn by moving beyond preexisting big data. In particular, I’ll show that by asking people questions, researchers can learn things that they can’t easily learn by just observing behavior. In order to organize the opportunities created by the digital age, I’ll review the traditional total survey error framework. Then, I’ll show how the digital age enables new approaches to both sampling and interviewing. Finally, I’ll describe two strategies for combining survey data and big data sources.
In chapter 4 (“Running experiments”), I’ll begin by showing what researchers can learn when they move beyond observing behavior and asking survey questions. In particular, I’ll show how randomized controlled experiments—where the researcher intervenes in the world in a very specific way—enable researchers to learn about causal relationships. I’ll compare the kinds of experiments that we could do in the past with the kinds that we can do now. With that background, I’ll describe the trade-offs involved in the main strategies for conducting digital experiments. Finally, I’ll conclude with some design advice about how you can take advantage of the power of digital experiments, and I’ll describe some of the responsibilities that come with that power.
In chapter 5 (“Creating mass collaboration”), I’ll show how researchers can create mass collaborations—such as crowdsourcing and citizen science—in order to do social research. By describing successful mass collaboration projects and by providing a few key organizing principles, I hope to convince you of two things: first, that mass collaboration can be harnessed for social research, and second, that researchers who use mass collaboration will be able to solve problems that had previously seemed impossible.
In chapter 6 (“Ethics”), I’ll argue that researchers have rapidly increasing power over participants and that these capabilities are changing faster than our norms, rules, and laws. This combination of increasing power and lack of agreement about how that power should be used leaves well-meaning researchers in a difficult situation. To address this problem, I’ll argue that researchers should adopt a principles-based approach. That is, researchers should evaluate their research through existing rules—which I’ll take as given—and through more general ethical principles. I’ll describe four established principles and two ethical frameworks that can help guide researchers’ decisions. Finally, I’ll explain some specific ethical challenges that I expect researchers will confront in the future, and I’ll offer practical tips for working in an area with unsettled ethics.
Finally, in chapter 7 (“The future”), I’ll review the themes that run through the book, and then use them to speculate about themes that will be important in the future.
Social research in the digital age will combine what we have done in the past with the very different capabilities of the future. Thus, social research will be shaped by both social scientists and data scientists. Each group has something to contribute, and each has something to learn.
