[jnorthrop]

I had a very similar idea about 15 years ago. I was working for a market research firm that measured the effectiveness of marketing and public relations campaigns. To quantify results we read, categorized and graded articles pertinent to the campaign.

Since we were analyzing thousands of articles a week (this is pre-www BTW) I thought we could leverage that dataset to identify patterns that could be used to predict the market. Unfortunately it turned out to be a lagging indicator and 20/20 hindsight isn't valuable.

I'll be interested to see if you can succeed with essentially the same strategy. Of course the publishing industry is a much different animal now, so maybe it'll work this time around. I'll be watching you closely.

If you are interested in chatting feel free to email me. My address is in my profile.

[raarky]

You also have competition from the big guns with access to stuff like machine readable news feeds:

http://thomsonreuters.com/products_services/financial/financ...

[dem]

I agree, predicting purely on lagging information is no good. We had this comment before and that's why we are currently working on distinguishing between a news stating a fact that occurred in the past, present or future. With that, we'll be able to present what the market thinks of the future price movements. For example, an author saying: "we expect copper to surge in the coming months", would be recognized as a future statement and factored in the future bullbear index. Or something like that.

[jnorthrop]

That's smart, and very cool. I recall the dollar signs in my eyes when I thought about the potential in getting a predictive system like this to work -- I hope you guys nail it.