This is the interactive element for Chapter 4. This element allows you to visualize the diminishing returns in inferential accuracy from sampling more social information under different environmental conditions described in the chapter. You can change two important properties of the environment. The first one is the skewness of the frequency distribution across events. Many environmental quantities follow highly skewed distributions in which a select few objects dominate the others (e.g., the distribution of personal wealth in a population). The second environmental property you can change is the spatial clustering of events. People tend to interact and form social ties with others who have similar sociodemographic, behavioral, and attitudinal characteristics—a phenomenon known as homophily.
In the figure below, you will then see how these environmental properties affect the accuracy-gain of drawing an increasing number of social samples. The figure shows the accuracy in inferring which of two events is more frequent as a function of the number of randomly drawn samples. Also visualized are the level of skewness and clustering you selected for the simulation.