Further on the trend following thing
Yesterday I blogged about the use of online news aggregators such as Google News to map trends. Further surfing on the topic yielded the current state of the art in such aggregators – Silobreaker is at it’s most basic another news aggregator. But it’s added value lies in it’s ability to analyse, group & visualise related news stories in a way much more intelligent than the likes of Google’s related story results.
For an example of how this fits in with my idea of a trend alerting system, see one of it’s bespoke topics – profit warnings. Historic data seems to back anything up to a year, and what Silobreaker calls a ‘360 degree’ view, you get quotes, blogs, media trends as well as the news. The trends graph can be used to compare the relative media interest in news subjects, or ‘entities’ – a welcome nod in the direction of the Semantic Web there, with users having the ability to add entities not already recognised.
Further on the Semantic theme there is a network function that produces graphs of related entities. The obligatory news to map function is also available, and extremely useful it is too – I just learned of the US airstrikes against Al Qaeda on Somali soil because of it. As with the trend function, a time range can be specified.
There are always room for improvements on machine learning, and Silobreaker is no different – the above US airstrike news item was listed as of Baghdad origin, which in itself seemed fine as source of the article was a UPI journalist in Baghdad, but there was no mention of the Somali bombing run over Somalia itself on the world map.
Registering gives you the ability to personalise among other things your list of news sources. I guess what I’m saying from all this is that Silobreaker does much of the heavy lifting I’d envisage a financial trend forecasting tool to do. What now is needed is an API to access this analysis – something I’d be hopeful for, considering their background in ‘open source’ intelligence.