What does "batch" and "batch_size" mean in word2vec skip-gram model?
A minibatch, is a group of (input,output) pairs that you present to your neural net in one pass (or epoch), without computing the stochastic gradient descent between two pairs (you only do it at the end of the minibatch, summing the errors over the pairs). This improve the speed and prevent over learning on single elements, thus improving learning. It also doesn't need to much memory since your batches are "mini". 

Some people call stochastic training when your mini-batch has a size of 1, and batch training when it has the size of your training dataset. 

You can get some nice explanations here.