Capsule networks seem to have been made to try and replace CNNs. It's been experimented with in the past to use CNNs on text data by doing word embeddings (word2vec, GloVe, etc.) and training it to classify text. People have also thrown things like LSTMs to take in the CNN features and give results like that.
With capsule networks looking to find characteristics and properties of the data it sees, is it possible to implement capsule networks to extract features and properties out of text data?
If it is possible, would there be any added benefit to use it over CNNs?