In the text classification methods, the text representation based on the Word2Vec ignores the weight of words in distinguishing text. The method of combining Word2Vec weighted by TF-IDF and CNN is designed. In news text classification, the importance of news title is always neglected. Therefore, this study proposes an improved TF-IDF method, which takes both news title and body into account. Experiments show that the news text classification method based on weighted word vector and CNN has a greater improvement than the logistic regression classification. And its effect increases by 2 or 3 percentage points than the un-weighted method.