Semantic network using word2vec
You can try converting your word representation into a document representation by simply taking the average over the word vectors for a document. For example, if a document has 9 words with (9, 200) dimensions, by taking an average over the words you can have a document representation with a dimension (1,200).
After you have your document-representation, you can use T-SNE to find similar documents. The documents with a similar topic or theme will cluster near each other. You can always improve the document representation by improving your word vectors.
Check this