Interactive Large-Scale Graph Visualization and Analysis for Social Networks

Dramatic popularity and prevalence of online social networking services have involved an increase of members publicly who articulate mutual “friendship” relations. Therefore, people have shown a great need to exchange information, share data, and adopt innovations in social networking applications. Data exchange has become the backbone of the economy on a global scale. In this paper, we investigate the Interactive Large-Scale Graph Visualization and Analysis of Social Networks that can process large-scale data. We have adopted a concrete large-scale corporate social networking site to realize this work; however, the approach can be easily generalized to other Social Networks. The problem is first stated as clearly as possible, and the social network is formulated as a joint optimization problem of graph selection. Then we have proposed some low-complexity search algorithms. The simulation results prove that our approach achieves good performance with a much lower computational complexity. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.