How Negative Sampling work on word2vec?

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During neural network training, it always adjust all neuron weight so that it learn how to do the prediction correctly. In NLP, we may face more than 100 k (or even 1M) words and it will cause performance (in term of time) concern. How can we reduce the training sample in a better way ?We have hierarchical softmax previously but word2vec introduces negative sampling methodology to resolve this problem.