Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions. It involves the understanding of social agents, the interaction among these agents, and the effect of these interactions on the social aggregate. Although the subject matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in contemporary social simulation originated from fields such as physics and artificial intelligence. Some of the approaches that originated in this field have been imported into the natural sciences, such as measures of network centrality from the fields of social network analysis and network science. In relevant literature, computational sociology is often related to the study of social complexity. Social complexity concepts such as complex systems, non-linear interconnection among macro and micro process, and emergence, have entered the vocabulary of computational sociology. A practical and well-known example is the construction of a computational model in the form of an "artificial society", by which researchers can analyze the structure of a social system. History Background In the past four decades, computational sociology has been introduced and gaining popularity . This has been used primarily for modeling or building explanations of social processes and are depending on the emergence of complex behavior from simple activities. The idea behind emergence is that properties of any bigger system do not always have to be properties of the components that the system is made of. Alexander, Morgan, and Broad, classical emergentists, introduced the idea of emergence in the early 20th century. The aim of this method was to find a good enough accommodation between two different and extreme ontologies, which were reductionist materialism and dualism. While emergence has had a valuable and important role with the foundation of Computational Sociology, there are those who do not necessarily agree. One major leader in the field, Epstein, doubted the use because there were aspects that are unexplainable. Epstein put up a claim against emergentism, in which he says it "is precisely the generative sufficiency of the parts that constitutes the whole's explanation". Agent-based models have had a historical influence on Computational Sociology. These models first came around in the 1960s, and were used