On Fri, Oct 2, 2009 at 1:00 PM, David Fisher <tib...@gmail.com> wrote:
> > > For the most part its just a frequency count of words over a short > time period, minus stop words, filtering out usernames (notice @foo is > never a trend) and URLs. How it combines "Wave OR Google Wave" I'm > unsure of, and then there's some basic spam filtering in there > additionally. I hope it isn't that naive -- do you know what they're doing, or are you speculating? For one thing, systems that count the unique individuals mentioning a term, rather than just raw term counts, are far more accurate in predictive modeling. Furthermore, Twitter has plenty of data to incorporate traffic and social network analysis to further improve this "buzz" analysis. FYI, I've been doing social network buzz analytics for about ten years and have some patents in that area (which don't belong to me, but to Nielsen/Buzzmetrics). Nick
