In other words, we can combine the original word space vectors and the DPL vectors in a way such that the resulting representation can still represent the semantics of the words being at the same time more suitable for sentiment analysis related tasks.
for each word in the vocabulary, we derived such representation by juxtaposing 9 the original 250-dimensional word space vector, which is derived through word2vec, and a DPL vector: the result of this operation is a new 253-dimensional representation.