With the growing trend towards a world where mobile objects are getting more and more interconnected, location information is increasingly becoming a recognized need for providing rapid and timely information to the social network users. This ability has led the way to an augmentation of existing social network sites with location-based features or the creation of new ones exclusively around geographic information. Within these Location Based Social Networks vast amounts of geographic information are allocated, which attracted the attention of researchers with various scientific backgrounds.
 One of the hot topics in the field of location-based social networks is mining similarities among users in the terms of location, time and semantic. In this research, we provide a comprehensive review of the methods and criteria used to measure the similarities among the users. We have categorized the existing research areas on this subject and depict a clearer and more suitable perspective for further studies. According to the results of this study, it can be stated that researches in this field have not yet reached a proper maturity and accuracy. In addition some criteria, that applied semantic information and content data, must be studied further in the future.