Community Strength Analysis in Social Network Using Cloud Computing

In large cloud services, the social network domain has provided the services of data analysis efficient and faster. The study has designed a Facebook application for the development of a programming interface environment. In the context of social cloud to access the cloud service is more expensive; this design consideration is presented to get the data from the callback service. The Edge Learning Web miner coordinates the links from the user request from different services, the user has given the request to generate and link the users and return the user request and response. In the Weight-Based Dynamic Link Prediction. The node tendency has increased and influenced the community. Experimental results show that strength analysis of the prediction accuracy is 97.66% in comparison with state-of-the-art solutions.