I agree that's an interesting comparison to make but I'm not sure of the answer. The original purpose of this work was not to generate word vectors but rather to evaluate whether we have enough data to start using deep learning algorithms. That an RNN trained on our data was able to learn word vectors with a significant amount of structure seems like a positive sign. But I don't know how the quality of these word vectors would compare to vectors generated by more standard word2vec algorithms.