Social network sites (SNS) have touched the lives of millions of people around the world. People share interests, ideas, photos, activities in the social networks with their family, colleagues, friends and acquaintances. However, the degree of interactions among members widely varies. According to a sociology principle, people with similar personality often interact with each other more frequently. A group of connected people with similar personality traits is termed as a homophily. In this paper, we develop a method to identify homophilies by analyzing the Big5 personality traits of users from their interactions in an egocentric network like Facebook. We observe that our homophilies correctly cluster ranged from 73 to 87 % users for different personality traits. We also present a novel validation technique to verify those extracted homophilies in real life. Note that we are the first to validate the extracted homophilies and compare those with baseline techniques from SNS usage in real life using an interview-based method. We notice that our validation results show different agreements ranged from 0.207 (fair) to 0.709 (substantial) among the raters of those homophilies in real-life.