Towards Information Diffusion in Mobile Social Networks

Abstract

The emergence of mobile social networks opens up opportunities for viral marketing. However, before fully utilizing mobile social networks as a platform for viral marketing, many challenges need to be addressed.Towards Information Diffusion in Mobile Social Networks.

Towards Information Diffusion in mobile Social network plays an important role in spreading information, ideas and influence among its members.Today, social networks have evolved into online social networks such as Facebook, Twitter, and Google+ that link People,computers,and the Internet, and in Mobile information spreading through social networks has changed from”word-of-mouth”.

Bluetooth and Wi-Fi Direct also extend cell infrastructure restrictions communications between mobile devices and offer numerous ad-hoc opportunities for communicatio between users.

As the essences of viral marketing applications are the diffusion of information through the’word-of-mouth’ network by a small number of individuals, projects reports on Towards Information Diffusion we deal with the problem of identifying a small number of people through whom information may be disseminated to the whole network as quickly as possible. Diffusion minimization is of course critical to applications for viral marketing.

Conclusion

We addressed the issue of identifying a small number of nodes that could disseminate information to the network as soon as possible.projects on Towards Information Diffusion We proposed two algorithms: the community-based algorithm and the distributed set-cover algorithm to solve the problem of minimizing diffusion from different aspects in mobile social networks.

In particular,the community-based algorithm leverages the community structure for selecting diffusion nodes from a social point of view,projects reports on Towards Information Diffusion mobile whereas the distributed set-cover algorithm identifies diffusion nodes based on the information gathered through distributed testing of messages.

Projects on Towards Information Diffusion Simulation results show that for both synthetic networks and Facebook trace,the community-based algorithm has the best performance.Despite the lack of global information, the distributed set-cover algorithm outperforms the Facebook trace approximation algorithm in terms of diffusion time.