Social network data analysis and mining applications for the Internet of Data

摘要

Social network analysis is an interdisciplinary topic attracting researchers from biology, economics,rnpsychology, and machine learning, with an existing long history based on graph theory. Itrnhas since attracted interests fromboth the research and business communities for a strong potentialrnand variety of applications. In addition, this interest has been fueled by the large success ofrnonline social networking sites and the subsequent abundance of social network data produced.rnAn important aspect in this research field is influence maximization in social networks. The goal isrnto find a set of individuals to be targeted with the aim to drive social contagion and generate arndiffusion cascade. We provide here an overview of the models and approaches used to analyzernsocial networks. In this context,wealso discussdatapreparation andprivacy concerns.Wefurtherrndescribe different kind of approaches based on centrality measures, which express a sociologicalrninterpretation of the data, and stochastic influence and information propagation techniques,rnwhich aim at modeling the underlying diffusion processes that govern social interactions.