title: word2vec for document classification
body: <p>I am learning how to apply word2vec for document classification, but I am struggling with two issues following:</p>
  
  <ol>
  <li><p>My dataset consists of users' commments; some comments have only one word (e. g. "husgmabb", or a HTTP link which I simply convert it as "URL"). Can I apply word2vec to a dataset that contains such one-word comments?</p></li>
  <li><p>My dataset is labelled as "spam" or "ham"; I want to represent each document as a vector in features embedded space, then build a NN to train them. Is it a proper way for document classification?</p></li>
  </ol>
  
  <p>Can anyone give me some explanation, as I am just a new text mining leaner.
  Many thanks!</p>