[rspeer]

This is cool, even if it seems kind of frivolous. Word embeddings work for emoji just like they do for actual words, and it's neat to see an idea for how to commercialize that directly.

I wish they had explained details, such as what two-dimensional non-linear projection they're using for their map.

I also don't see it fully explained how they're getting representations of sequences of emoji. They explain how their RNN handles sequences of input words, but the result of that is a vector that they're comparing to their emoji-embedding space. Does the emoji-embedding space contain embeddings of specific sequences as well?

[wxs]

We use t-SNE for the projection! We do mention it somewhere in there. Could maybe be more clear

The sequences of emoji we ended up glossing over here (difficult balance making these concepts as accessible as possible). In the app we can beam search to predict combos, just as you would in sequence to sequence learning. That's not demo'd on the live website though.