how to build word2vec content based recommendation?
You can find a number of blogs teaching the use of Word2Vec,


Introduction to Word Embedding and Word2Vec
A Beginner's Guide to Word2Vec and Neural Word Embeddings


If you are building a hotel recommendation system, I think the name of the hotel is not a good feature. Users are less concerned with the name of the hotel than its location or description provided.


You can take a small description from the user and the location in which they would like to search for the hotel. Using Doc2Vec, convert the description ( text ) into a fixed-sized vector ( embedding ). Find a hotel whose description is the most similar to the one provided by the user ( maybe using Cosine Similarity or any other measures ). 
Before this find a hotel that is close to the location provided by the user ( say a hotel which lies in a radius of 2 km from the given location ).


Using these two factors, you can prepare a list of hotels whose location and description match the user's needs.