While the correlation for 400-dimensional embeddings shown in Table 1 is .661, the correlation of 60-dimensional embeddings is only .568.
even though we show that the information in 400-dimensional embeddings that is relevant for sentiment can be condensed into a single dimension, hundreds of dimensions seem to be needed if we use word2vec to collect sentiment information.