I've always wondered if there was a way to make some money in the market by performing lexical analysis of news articles about stocks and gauging the performance of those stocks based on the contents of the article.
So, you'd train your software by analyzing every news article you could find over the past N years for every company in the market you're targeting. It would look for words or phrases that occurred with higher frequency a few days before stocks made significant moves in either direction.
I suppose you'd probably want to weight the source as well, articles sourced from the WSJ might earn a better reputation than ones from the NY Post for example.
At some point there would hopefully be enough confidence in the data that you could test it out with $1000 or something small; news-driven automation... There are enough people who buy and sell on news and opinion pieces that there may be enough fat there to make some profits.
There was actually an interesting study done on quarterly earnings releases that had some interesting implications as far as "soft data" versus hard numbers:
http://ideas.repec.org/p/fip/fedgif/951.html
There was a company "Quant the News" that launched a product that did sentiment analysis on company related news, but their website no longer exists. http://www.crunchbase.com/company/quant-the-news
The focus on number crunching seems contrary to advice given by Warren Buffet and other successful investors about investing in what you know.
i.e. "I think the market is under-estimating the impact of Product X, I'll invest in that company" versus "Analyze market cap, yearly revenue...."