The invention discloses a domain adaptation-based word division method of social network text. Through building an integrated neural network and using a self-training learning method, cross-domain news corpus and labeled data and unlabeled data in a social network are utilized to train an integrated neural network model. The method specifically comprises: dividing the social network text into labeled and unlabeled datasets, and using the datasets as input; using the news domain corpus as source corpus, and pre-training source classifiers on the news source corpus; integrating the source classifiers through a manner of assigning weights to the source classifiers; using the social network corpus to train the integrated neural network model; and utilizing the well-trained integrated neural network model to carry out prediction, and thus improving an effect of word division of the social network. The method can be used to solve the problem of a poor effect caused by very insufficient data in the social network, and can effectively improve the effect of word division of the social network text.