Digital Twin is defined as a realistic digital model of an object's physical state, representing its interaction with the environment in the real world. The research on Digital Twin has been advancing intensively in recent years. As a result of an emerging and broad research topic, various interpretations and Digital Twin applications have been developed. In this scenario, there is an opportunity to research the Digital Twin types and understand the concept evolvement. This paper provides an overview of the Digital Twin concept, classifies the existing body of literature, and discusses the Digital Twin evolution. Therefore, this research applies a combination of methods, including bibliometrics, natural language processing, and content analysis. The results show an expansion of Digital Twin's role from an enabler of cyber-physical systems to a product lifecycle data integration and processing platform.