Realtime Twitter / capital market analysis in Haskell. Also, anyone hiring? (ego.fm)
Just wanted to share my hobby project with y'all - it reads Twitter and tries to classify each message as "bullish" or "bearish", then keeps track of which ticker symbols are mentioned, calculates the most mentioned each hour and creates a leaderboard. The backend is Haskell (Snap framework) and Redis, the frontend is Raphael.js and JQuery.<p>As an aside, I recently have found myself unemployed - anyone hiring or have some contract work they need done? Take a look at my github account at http://www.github.com/texodus for some of my code, including (soon) this site.
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[ 2.9 ms ] story [ 50.4 ms ] threadAs an aside, I recently have found myself unemployed - anyone hiring or have some contract work they need done? Take a look at my github account at http://www.github.com/texodus for some of my code, including (soon) this site.
My company is looking for employee #4, we do high frequency trading:
http://meshcapital.com/Careers.html
http://ego.fm/screenshot.png
The red & green spikes represent individual polls of Twitter, and the overall sentiment regarding the ticker - the dotted line is the cutoff for which scores are used to calculate the leaderboard.
I live in Brooklyn, so Jersey may work.
However, I do wonder if it would be easy to spam Twitter and thereby ruin its usefulness for real-time data mining. If Twitter can be used to accurately track trends, as soon as everyone knows trends are being created based on Twitter, then they can manipulate it, similar to pump-and-dump spam schemes we've seen on various financial news boards, like Yahoo, Motley Fool etc.