We know intuitively that people affect each other, but it’s hard to say how much. What if we knew? Imagine we could pinpoint exactly who caused other people to do things, and how much–whether that was shopping, going to the doctor, voting, consuming media, or any other action. What if we also knew how much this happened in general, and how it varied from context to context?

In this talk, I’ll explain a new method for measuring the effects of interactions over time, which we call “Social Value.” Most of the solutions for this age-old challenge have been based on social media, where we infer influence from follower counts or reposts, but which aren’t tied to outcomes. They haven’t been falsifiable. Social Value solves for this, and gets us beyond guesswork. Although we are in the early days of the research, it’s also opening up theorizing and practice around why and how people lead and follow. In this talk, I’ll discuss the general concept of Social Value, how we’ve tested and validated it, and what we’ve found, including connections to personality, race and social capital. I’ll also cover the method’s potential for network research and use in social science more broadly.