Social network analysis attracted interests from both the research and business communities for a strong potential and variety of applications. In addition, this interest has been fuelled by the large success of online social networking sites and the subsequent abundance of social network data produced. A key aspect in this research field is the influence maximization in social networks. In this paper we discuss an overview about the models and the approaches widely used to analyse social networks. In this context, we also discuss data preparation and privacy concerns also considering different kind of approaches based on centrality measures.
Remarks of Social Data Mining Applications in the Internet of Data / Cuomo, S.; Maiorano, F.; Piccialli, F.. - 22:(2019), pp. 944-951. [10.1007/978-3-319-98530-5_86]
Remarks of Social Data Mining Applications in the Internet of Data
Cuomo S.
;Piccialli F.
2019
Abstract
Social network analysis attracted interests from both the research and business communities for a strong potential and variety of applications. In addition, this interest has been fuelled by the large success of online social networking sites and the subsequent abundance of social network data produced. A key aspect in this research field is the influence maximization in social networks. In this paper we discuss an overview about the models and the approaches widely used to analyse social networks. In this context, we also discuss data preparation and privacy concerns also considering different kind of approaches based on centrality measures.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.