The invention relates to a keyword automatic extraction method based on distributed expression word vector calculation. The method automatically generates characteristics, and preferably solves keyword automatic extraction. The steps of the method are as followings: step 1, obtaining a training original dataset; step 2, performing preprocessing on a training set and a test text, including removing punctuation, digits, stop words, and filtering word characteristics; step 3, after the training set is obtained, through training of a linguistic model, converting the training set into a word vector table; step 4, through a distance calculation method, calculating the distance from a keyword word vector to a to-be-tested text; step 5, by different distance calculation methods, respectively obtaining arithmetic average semantic distances between distributed expression word vectors of all keywords of a field keyword set and distributed expression word vectors of all words of the test text, so as to select and sort. The method provides a new thought for extraction of keywords, semantic information of a dataset is fully used, and accuracy of automatic extraction is substantially improved.