Improving information diffusion on social networks by utilizing the SOM neural network

Wireless The Internet world has generated new types of communication between humans. In this way, the social networks that are a graph of people, have found a special situation. Today, the growing and updating of the social networks have led to the emergence of new markets, innovative and powerful businesses. Information diffusion and maximization of it play a critical role in the social networking services. Marketing for increasing product sales, intrusion methods, technology spread to political activities, medical analysis, and political popularity, all of them are the subjects, where information diffusion is very useful for them. One of the key issues in these networks is to find a collection of the most influential people on a social network to spread information for the largest network range. The simulation results show that the proposed algorithm performs better than the other similar approach so-called IM-LPA. Moreover, it is capable to find the optimal solution in terms of the amount of information diffusion over time and computational overheads, as compared with others.

Keywords:

social networks , Information diffusion , influential node , SOM neural network