Survey on a Model for Examining the Role of Nodal Attributes in Dynamic Social Media Networks Using Natergm

Social media networks are dynamic. All things considered, the request in which organize ties create is an imperative part of the system flow. This examination proposes a novel dynamic system demonstrate, the Nodal Attribute-based Temporal Exponential Random Graph Model (NATERGM) for dynamic system investigation. The proposed demonstrate centers around how the nodal traits of a system influence the request in which the system ties create. Worldly examples in social media networks are demonstrated in light of the nodal qualities of people and the time data of system ties. Utilizing social media information gathered from a knowledge sharing group, observational tests were led to assess the execution of the NATERGM on distinguishing the transient examples and foreseeing the qualities without bounds networks. Results demonstrated that the NATERGM showed an improved example testing ability and an expanded expectation precision of system attributes contrasted with benchmark models. The proposed NATERGM show clarifies the parts of nodal qualities in the arrangement procedure of dynamic networks.