We tuned the word embedding parameters method, corpus and dimensionality, while holding other parameters constant (dropout = 0.5, decayrate = 0.5 and layersize = 2).
we tested the methods Word2vec using the Gensim Word2vec package (Řehůřek and Sojka, 2010) and pretrained Glove word embeddings (Pennington et al., 2014).