Research of micro-blog diffusion effect based on analysis of retweet behavior

Research on the diffusion effect of micro-blog plays an important role in improving marketing efficiency, strengthening monitoring public opinion and accurately discovering hotspot etc. To solve the problems not taking users' differences into consideration in the previous research, this paper proposes an algorithm to predict scale and depth of retweet massages based on analysis of retweet behavior. With the combination of LR algorithm and nine related features extracted from micro-blog users themselves, their relationships and micro-blog contents, we proposes a prediction model of retweet behavior. Based on this model, we proposes an algorithm to predict the diffusion effect, which considers the character of information spreading along users and does statistical analysis of adjacent users iteratively. Experimental results on Sina micro-blog dataset show that the algorithm has a prediction accuracy of 87.1% and 81.6% in scale and depth respectively, which indicates the model works well.