New trends in influence maximization models.

The growing popularity of social networks is providing a promising opportunity for different practical applications. The influence analysis is an essential technique supporting the understanding of real-life activities. Accordingly, certain reviews and surveys have been presented, focusing on models, methods, and evaluation aspects related to social influence analysis. However, the ultimate goal is that the background social influence analysis methods developed in research could be employed in real applications. In this context, social influence analysis still remains a number of challenges including the privacy of the massive networks that have been recently mentioned by researchers. Motivated from these facts, in this paper we provide a state-of-the-art survey on the influence analysis techniques in addressing these challenges. In this detailed survey, we divide the diffusion models into two categories, individual and group node-based models. Our primary focus is to investigate the research methods and techniques and compare them according to the above categories. In the sequel, we especially further provide an overview of the existing methods for influence maximization under privacy protection. The recent advanced applications of social influence are also surveyed. In the end, open issues are discussed to enable the researchers to a better understanding of the present scenario and suggest several potential future directions for research in influence maximization. • A comprehensive literature review of pertinent studies on social influence analysis. • A detailed taxonomy of individual node and group-based influence analysis models. • Parallel influence maximization approaches and their methods are illustrated. • The main contribution of the survey is to highlight the research trends for analysis of social influence under privacy protection. • Challenges/limitations in influence analysis and their perspective research direction are discussed. [ABSTRACT FROM AUTHOR]