Method for quantitatively predicting microblog forwarding breadth and depth

The invention belongs to the technical field of information and data processing, and discloses a method for quantitatively predicting microblog forwarding breadth and depth, which comprises the following steps: dividing extracted features into user features, microblog features and social features, and storing the user features, the microblog features and the social features into a file; reading all processed data, taking 70% of the data as a training data set, and taking 30% of the data as a test data set; extracting features useful for the training model in the training data set; establishing a model by using an improved random forest algorithm, and predicting the forwarding breadth and depth of each microblog; and testing the accuracy of the algorithm by using test set data, and calculating an average absolute percentage error and prediction precision. According to the invention, the propagation breadth and depth of user forwarding behaviors are predicted by using a machine learning algorithm; and the impro