Dynamic Multi-Path Relationship: Preserved Embedding for Social Network

In the contemporary era, human beings are living in a digital era, in which the issue of social network analysis has been constantly scrutinized and discussed. While the research regarding static embedding approaches has made significant progress, these approaches fail to deliver comprehensive solutions to circumstances with respect to dynamic embedding. This is a major defect, as the social network is constantly changing and evolving in a world that is developing rapidly and totally unpredictably. Therefore, this research paper focuses on dynamic social network embedding and investigates how to preserve multi-path relationships in dynamic social networks efficiently under rapidly changing topologies. The research is conducted through systematic and critical reviews of different varieties of dynamic embedding algorithms and models, followed by a comprehensive comparison. This research paper figured out that dynamic models and algorithms excel in the analysis of network users connections in so many ways, which is mainly because of their ability to capture fleeting information and leverage information as social networks change and evolve continuously over time.