Using LSTM for multi label classification

I am trying to use LSTMs to train and predict authors using reviews data and metadata

author  phone  country day     review
james   iphone chile   tuesday the book was really amazing


How do I pass all these features into the network?

Since the review of an author is bound to change in terms of the number of words being used in the review, I would suggest using a Keras Sequential() model to build an LSTM encoder for the review itself. The final hidden layer of the review LSTM encoder can then be fed into another LSTM encoder with 3 words (phone, country, and day). Think of the last LSTM encoder as a sequential 3 worded message. The final layer of this LSTM can then be joined with a softmax layer to predict the author.