Different from the previous word embedding generation methods, SLTM generates word embeddings based on the global label-specific topic information (i.e., the topical embedding space).
we further compare the quality of word embeddings learned by SLTM and three widely used methods: Word2Vec (W2V) (Mikolov et al., 2013), subword information Word2Vec (siW2V) , and SSPMI (Levy and Goldberg, 2014).