title: How is the window size affect word2vec and how do we choose window size according to different tasks?
body: <p>For example, if I choose two window size, 5 and 50, and train the word2vec model, will the 50 one takes more time to train? Will the embeddings of the 50 one concentrates more on semantics of the text and the 5 one concentrates more on single word?
  BTW, above two questions are just my thinking/exmaples of what I am seeking. My real question is just the title &quot;How is the window size affect word2vec and how do we choose window size according to different tasks?&quot;</p>