[baronofcheese]

A friend and I did something related to this in a project, where we attempted to analyze a hash tag, by fetching the latest 100 tweets about that hash tag. It is very useful in trending topics. For instance searching for "Stuart" right now reveals a lot of other relevant tags and attempts to find out what the general mood is of the words used in the tweets doing a simple Sentiment Analysis using AFINN. Try it here: http://hashtagram.dk/?t=stuart#hashtags (might get unavailable due to many visits, and don't mind the broken Instagram images at the bottom, site needs updating due to API changes). If for some reason the site does not work, see a static version here: http://imgur.com/EQzMrUP

[tabrischen]

It might be interesting to do a separate one just on Instagram. I have no idea what half of the trending hashtags on Instagram means and a picture speaks a thousand words.

[baronofcheese]

The Instagram pictures were there to back up the understanding of a hashtag generally. For under the world cup, it was really easy to find out what #worldcup2014 was about. Interestingly refreshing the page for a specific page during some kind of event, such as the world cup one, or during 24 Hours of Le Mans, it is easy to follow what people say about it. In the Le Mans case it was also quite easy to follow that for instanced someone crashed their as the sentiment drastically went to the negative side, and you could back that up with pictures of the crash on Instagram.

But I agree, a separate one analyzing the pictures could be valuable as well. However, Instagram pictures often don't contain much text apart from a wall of hash tags. So the text might not be super important to analyze. Anyways, picture analysis might be slightly more difficult and more resource intensive than text analysis, but very interesting as well.

[amtmz]

Awesome project!

[baronofcheese]

Thanks a lot. Yours is pretty cool too. However, I agree with other people saying that the element of the bubbles moving might not be the best indicator of frequency of mentions of that word in tweets.

Not sure, how it could be done otherwise, but it needs to be thought a bit more about. Maybe do something more to the bubbles, like coloring and filling them. Maybe even just showing a number inside the bubble if there is room, or when highlighted.

Also, instead of refreshing the page, you could consider something like Socket.io between the web page and your node.js server to update the values. There might be other alternatives to Socket.io, but then you won't have to refresh the entire page.

Anyways, keep up the good work :)