Examining link prediction and node connectivity objectives in social networks: Comprehensive review

Abstract

A social network plays a pivotal role in modern society, facilitating communication, information dissemination and social interactions. As systems such as this one continues to grow in complexity and scope, yet the challenges become identifying the absence of a node as well as ensuring an uninterrupted connection. These comprehensive reviews analyze the objectives of link prediction and node connectivity in the context of social networks. The objective of link prediction and node connectivity in social networks is to pave the way for future analysis in network design and security. This review analyze the node connectivity and link prediction, which is represented as graph G= (s, e) where s denotes the number of vertices and e denotes the number of edges. It highlights the effectiveness of linkages along with node connectivity and forecasting future interactions in enabling the development of targeted marketing strategies and personalized recommendation systems. The significance of node connectivity analysis is to evaluate the resilience and robustness of social networks. It explores the identification of critical nodes and the impact of their removal on network fragmentation, thus emphasizing the importance of developing effective strategies to enhance network resilience and security. Furthermore, the review emphasizes the interplay between link prediction and node connectivity in advancements of link prediction techniques that can booster the accuracy of node connectivity in social networks. It underscores the implications to understand the network dynamics as well as predicting the development of security and efficient social network infrastructures.