How best to embed large and noisy documents
Doc2vec and similar algorithms are useful methods to create document embeddings.
You should try to include as much data and metadata as possible.
The size of the documents does not matter much because they will be project into a fixed dimensional embedding space.
As far as noise, the effect will be task specific. If you are doing similarity analysis and clustering, you can use approximate methods which are robust to noise.