Abstract

By now, personal life has been invaded by online social networks (OSNs) everywhere. They intend to move more and more offline lives to online social networks. Therefore, online social networks can reflect the structure of offline human society. A piece of information can be exchanged or diffused between individuals in social networks. From this diffusion process, lots of latent information can be mined. It can be used for market predicting, rumor controlling, and opinion monitoring among other things. However, the research of these applications depends on the diffusion models and methods. For this reason, we survey various information diffusion models from recent decades. From a research process view, we divide the diffusion models into two categories—explanatory models and predictive models—in which the former includes epidemics and influence models and the latter includes independent cascade, linear threshold, and game theory models. The purpose of this paper is to investigate the research methods and techniques, and compare them according to the above categories. The whole research structure of the information diffusion models based on our view is given. There is a discussion at the end of each section, detailing related models that are mentioned in the literature. We conclude that these two models are not independent, they always complement each other. Finally, the issues of the social networks research are discussed and summarized, and directions for future study are proposed.

Highlights

  • The term “social networks” (SNS) was first used by Barnes [1] in the Human Relations Journal in1954

  • We do not know why the information flows to this direction in social networks, we have seen the advantages of a social network in information diffusion

  • The explanatory models presented in this paper aim to examine the information diffusion process and elucidate the factors that affect it in an attempt to explain this phenomenon

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Summary

Introduction

The term “social networks” (SNS) was first used by Barnes [1] in the Human Relations Journal in. Much research effort has been put into analyzing information diffusion, with most studies investigating which factors affect information diffusion, which information diffuses most quickly, and how information is disseminated [2,3] These questions are answered using information diffusion models and other methods, which play an important role in understanding the diffusion phenomenon. If A posts some information, both B and C will each have a different perspective on the information, which will influence how they respond and whether they further propagate it through the network These factors aid in the understanding of which node will be the destination for the future diffusion of the information, i.e., the prediction of information diffusion.

Aims of the Explanatory Models
The Basic Epidemics Model
The SI Model
The SIS Model
The SIR Model
The SIRS Model
Epidemic Models in Social Networks
Method
Community Influence
Influence Maximization
Aims of Predictive Models
Future Challenges
Influence Analysis
Combine Group Status with Network Structure Research
Prediction of Information Diffusion
Discussion and Conclusions
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