Abstract We study an interesting phenomenon of social in?uence locality in a large microblogging network, which suggests that users’ behaviors are mainly in?uenced by close friends in their ego networks. We provide a formal de?nition for the notion of social in?uence locality and develop two instantiation functions based on pairwise in?uence and structural diversity. The de?ned in?uence locality functions have strong predictive power. Without any additional features, we can obtain a F1-score of 71.65% for predicting users’ retweet behaviors by training a logistic regression classi?er based on the de?ned functions. Our analysis also reveals several intriguing discoveries. For example, though the probability of a user retweeting a microblog is positively correlated with the number of friends who have retweeted the microblog, it is surprisingly negatively correlated with the number of connected circles that are formed by those friends.