Understanding Word Embeddings
The original papers written by Thomas Mikolov are word2vec and doc2vec.

Lecture notes given by Richard Socher is simple to understand.

word2vec explained gives an intuition how the negative sampling in word embedding works. Not the whole algorithm though.

Nevertheless, there are implementations in various languages and libraries explaining how it works in their docs.

Python - gensim, Tensorflow

java - deeplearning4j