This example shows the relationship between follower and following counts for a subset of Twitter users, revealing a dense clustering pattern near the origin with sparse outliers at higher values. The R code first retrieves JSON data from a ScraperWiki SQL endpoint, converts it into a data frame using the `rjson` package, and then renders a smoothScatter plot—a base R function that uses hexagonal binning and color density to visualize overlapping points. The plot is restricted to a 0–5000 range on both axes to focus on the majority of users while still exposing the distribution’s shape. The approach highlights typical user behavior rather than individual outliers.