A New Correlation-based Information Diffusion Prediction

For predicting the diffusion process of information, we introduce and analyze a new correlation between the information adoptions of users sharing a friend in online social networks. Based on the correlation, we propose a probabilistic model to estimate the probability of a user's adoption using the naive Bayes classifier. Next, we build a recommendation method using the probabilistic model. Finally, we demonstrate the effectiveness of the proposed method with the data front Flickr and Movielens which are well-known web services. For all cases in the experiments, the proposed method is more accurate than comparison methods.