Social Network Mining (SNM) has become one of the main themes in big data agenda. As a resultant network, we can extract social network from different sources of information, but the information sources were growing dynamically require a flexible approach. To determine the appropriate approach needs the data engineering in order to get the behavior associated with the data. Each social network has the resources and the information source, but the relationship between resources and information sources requires explanation. This paper aimed to address the behavior of the resource as a part of social network analysis (SNA) in the growth of social networks by using the statistical calculations to explain the evolutionary mechanisms. To represent the analysis unit of the SNA, this paper only considers the degree of a vertex, where it is the core of all the analysis in the SNA and it is basic for defining the relation between resources and SNA in SNM. There is a strong effect on the growth of the resources of social networks. In total, the behavior of resources has positive effects. Thus, different information sources behave similarly and have relations with SNA.