PREDICTING THE NETWORK TRAFFIC CREATING USERS FROM USER POSTING BEHAVIOR IN ONLINE SOCIAL NETWORKS

Mrs.R. Gomathi; Mrs.N. Vijayalakshmi

Volume : VII, Issue : II, February - 2017

PREDICTING THE NETWORK TRAFFIC CREATING USERS FROM USER POSTING BEHAVIOR IN ONLINE SOCIAL NETWORKS

Mrs. R. Gomathi, Mrs. N. Vijayalakshmi

Abstract :

Social media acts a significant role among the media users. Social networks such as facebook, google+, foursquare, LinkedIn etc., have become extremely eminent over the world. OSN traffic is growing quickly and becoming significant, they want to learn the evolution of the traffic pattern of OSNs. In this paper, we propose an efficient swarm model to predict the traffic creation from user behavior model. In general, there prevail 12 types of social media users. Each user defines unique characteristics. The intention of this study is to discover the sorts of traffic creating social users. Inspired by the cat behavior, the user behavior model is designed into two modes, namely, i) Seeking mode and ii) Tracing mode. Firstly, the counts of cats are initialized. By estimating the optimal fitness value from support and confidence values, the users are placed to its relevant classes. By updating its position and velocity of each user, the traffic creating users from their spatial data is predicted. An experimental analysis shows the effectiveness of the systems.