sayit

This is awesome! My input had exactly the results I expected. Thanks for creating this tool, bookmarking!

This is a really useful tool. It works so smoothly on my mobile.

Happy to hear :)!

Useful little tool! Reddit humor subs are so damn specific, it can be hard to find them all.

This is great, and works flawlessly!

This is seriously amazing man! Interesting to see how different subject-areas network themselves differently. For example, comparing "r/permaculture" to "r/linux". Also, looking…

Interesting finds: * /r/askscience is nested at the center of defaults (I think a lot of older, famous subs will end up highly connected) * /r/relationship_advice is kind of a…

It's a cool tool, but it seems very biased towards bigger subs. If you let it loose on a small sub it will emphasize that big, kinda-but-not-really related subs over…

It's a shame since this tool would be particularly useful for recommending small subs. I don't need it to tell me about big subs, since I already know them.

This is a great idea for a project, the 'users who also posted' metric seems to have worked really well. The site seems to fail to load the 'hot' items for the subreddits when I…

That sounds like Content Blocking kicking in - that's only active in Private Browsing by default: https://support.mozilla.org/en-US/kb/content-blocking I note that page says "By…

Thank you so much! I opened an issue here: https://github.com/disconnectme/disconnect-tracking-protection/issues/67

Good tool if possible add option to view result data in tabular format with no of subscribers. As this way its difficult to use.

That's a cool tool. And useful extension would be if it preserves the location history if you navigate topics, so that you can go back.

Good call. I was worried that I'd "spam" the browser history and people who are coming from reddit or HN would never go back to where they came from :)

I was sort of expecting to be able to click through to the subreddit...

> The relationship is determined by a metric "users who posted to this subreddit also post to...". I'm interested, could you share with us the the entire metric you used to…

It is jaccard similarity https://en.wikipedia.org/wiki/Jaccard_index Also I described it a bit more here:…

You indicated that you used the Pushshift.io datasets, but how did you compute Jaccard Similarity on a dataset of 38M?

I didn't use pushshift, sorry. The data was collected from bigquery, stored locally into CSV files, and then I just wrote a node.js script to compute similarities.

Is this built on top of your work on yasiv before?

It would be fair to say so. The core layout is the same with a bit more polished overlap removal and animation.