A Visual Tool for Exploring Word Embeddings

I built a visualization to explore embeddings a few years ago, but never posted it more broadly. So here it is! http://blog.echen.me/embedding-explorer/

These are GloVe embeddings projected into 2D, colorized via k-means in the original space.

You can see, for example, that the cluster in pink at the bottom right is a cluster of names.

Names Cluster

And the cluster in red on the right is a cluster of geographical terms.

Geography Cluster

We can click on one of these points ("iceland") to see its nearest neighbors in the high-dimensional space (mostly other countries!) as well as other points that belong to the same cluster (Cluster 18 is this red cluster).


We can also inspect each individual embedding dimension, to understand what it's picking up. Embedding Dimension 1, for example, seems to capture sportiness.

Embedding Dimension 1

We can also slide through the points based on their embedding dimension to get a better sense:

Embedding Dimension 1 Slide

Anyways, play around with the explorer here, and feedback is always welcome!

Edwin Chen

Surge AI CEO: data labeling and RLHF, designed for the next generation of AI.

Need high-quality, human-powered data? We help top AI and LLM companies around the world create powerful, human-labeled datasets.

Ex: AI, data science at Google, Facebook, Twitter, Dropbox, MSR. Pure math and linguistics at MIT.

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