The word embeddings for the above two domains were trained by us on the respective corpora using word2vec (Mikolov et al., 2013) which employs a two-layer neural network and is by far the most widely used word embedding technique.
we ran word2vec with skip-gram of a fiveword window to construct word vectors of 500 dimensions, as recommended by previous studies 7 .