The invention discloses a social platform rumor detection model construction method and prediction method based on comparative learning, and the method comprises the steps: carrying out the expansion and enhancement of an original data set through event enhancement, inputting the enhanced data into comparative learning and a graph neural network, and carrying out the self-supervision graph representation learning, and obtaining a model under no-label training. And then training a network model by using part or all of the labeled data, finely adjusting the model by using supervised information to obtain an embedded representation representing source blog article information, and finally inputting the embedded representation into a neural network classifier to obtain a rumor classification result. According to the graph neural network-based comparative learning method and the event enhancement strategy, the current situations that rumor data sets are scarce and data set labels are difficult to manufacture under the real condition are relieved. Furthermore, the learned rumor embedded representation is input into the neural network classifier, so that the purpose of online network platform rumor detection is achieved.
Social platform rumor detection model construction method and prediction method based on comparative learning