https://www.scientificamerican.com/article/friends-of-friends-can-reveal-hidden-information-about-a-person/

People generally spend time with others who are like them, making it easy for data scientists to infer individuals’ attitudes or personality attributes by analyzing their online and real-world social networks. Researchers call this tendency to seek out like-minded people “homophily.” Think of the old adage “birds of a feather flock together,” says Johan Ugander, a management science and engineering researcher at Stanford University, who studies this topic.

But in a twist on the topic, Ugander and his graduate student Kristen M. Altenburger have found that some people are consistently drawn to those with certain dissimilar attributes. The researchers call the variation introduced by this phenomenon “monophily.” Scientists previously assumed that heterogeneity would make it harder to draw conclusions about people based on friend networks. But Ugander and Altenburger’s research demonstrates that monophily produces an effect whereby a person’s friends of friends are similar to them in ways that immediate friends may not be. This could make it easier than anticipated for scientists to infer personal characteristics that might otherwise remain hidden—and is one more way for data miners to trace personal information.