Retweet Behavior Prediction Based on a New Social Influence Measurement in Microblogging Network Network

Nowadays, retweeting behavior is considered a substantial behavior to analyze information dissemination in the microblogging network. To understand the underlying mechanism of information dissemination and analyze the evolution of the dissemination corresponding to a given original microblog, user retweeting behavior prediction has recently gained considerable attention. In this paper, we first introduce the four key influential factors that affect the prediction performance of user retweeting behavior then we propose a new measurement based on the random walk for the social influence measurement. Secondly, our defined influential factors are fed into a logistic regression classifier model to estimate the activation of any potential user at each time point. Next, we generalize our model so that, by assuming that we have some activated users concerning the dissemination of a given original microblog at each time point, the future activated user set concerning the dissemination of a given original microblog can be predicted at the next time point. Unlike other comparative models, our prediction model can illustrate the evolution of dissemination and predict the retweeting behavior of all potential users through the dissemination of any original microblog in the microblogging network. Finally, based on the real Twitter microblogging dataset, the experimental results illustrate by the contribution of our defined influential factors and presenting an efficient measurement of the social influence factor, we can simultaneously ensure both the generalization of the proposed model and obtain more accurate predictions in comparison to other baseline methods.

کلیدواژه ها:

influential factors ، social influence ، retweeting behavior prediction ، information dissemination ، generalization.