Content diffusion prediction in social networks

Social networks are valuable resources for analyzing users' natural behavior. User profile information, social links and interchanging opinions among users in these networks can be used by social analyzers to discover mental and behavioral patterns of users in social networks. In this paper, news agencies are used as the social media to detect effective factors of diffusing contents in public. We believe that the volume of comments on content show how well the content has spread and attracted attentions. As a result, we extract features of contents to predict volume of comments. To achieve this goal, content of the news articles and its publication time are considered as two critical factors. A novel method for prediction of content diffusion is proposed and its accuracy is evaluated. The promising results of our experiments indicate that these factors can gain accuracy of at least 70%.