Since the concept of entitymetrics was first introduced in 2013, entitymetrics has been applied to measure the impact of entities as well as to gauge the knowledge usage and transfer anchored on entities for knowledge discovery. This concept extends informetrics by quantifying the importance of various types of entities such as concept, dataset, and domain entities buried in a large amount of full-text collections. Entitymetrics uses entities for knowledge usage as well as discovery. We claim that it is the next generation of content-based citation analysis in that it aims to utilize entities to create a knowledge graph for scientific discovery where entities are connected to each other either by citation or predicate relation. In this talk, the previous studies employing entitiymetrics are summarized and the limitations of the current approaches are discussed. In addition, the future directions of entitymetrics are suggested.