Word2Vec

Word embeddings trained on UK Twitter content (II)The total number of tweets used was approximately 1.1 billion, covering the years 2012 to and including 2016.Settings: Skip-gram with negative sampling (10 noise words), a window of 9 words, dimensionality of 512, and 10 epochs of training. After filtering out words with less than 100 occurrences, an embedding corpus of 470,194 unigrams was obtained (see embd_voc). The corresponding 512-dimensional embeddings are held in embd_vec.bz2.