Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.