The U.S. is a mere three months away from choosing who will be its leader for the next four years. The semantic web is a supporting player in the action.
This week, of course, saw the debut of the Twitter Political Index (Twindex), a joint effort between Twitter, Topsy, and the Mellman Group and NorthStar Opinion Research polling groups. Since the Semantic Web Blog last spoke with Topsy execs here, the company has refined its sentiment analysis to the point where it could be released for the Twindex. The sentiment analytics engine ingests hundreds of millions of English-language tweets a day and computes sentiment for all terms in Twitter, though that’s not publicly available yet.
In its Twindex incarnation, Topsy aggregates the underlying sentiment score minute by minute, and then that is rolled up into an hourly and daily score for each candidate, says Rishab Aiyer Ghosh, co-founder and chief scientist at Topsy Labs. Behind the scenes, “that score is normalized so that it is on 0 to 100 scale comparing to all the other terms people talk about,” he says, which is important for keeping perspective on the candidates in context relative to whatever else may be on the mind of the collective social media conscience. It also is weighted to include the scores of the previous two days before its publication at the end of the day, and smoothed out so that it doesn’t jump around in helter-skelter fashion.