SAN FRANCISCO, CA and AUSTIN, TX--(Marketwire - Dec 10, 2012) - TrendPo (www.trendpo.com), a website that ranks all politicians and issues on buzz, correctly predicted all 11 US Governor races and 75% of the contested congressional races. Now, he's using his technology to predict major political issues like the Fiscal Cliff.
Each day, TrendPo's engine scans an average of 700 news articles and 2,000 politicians' Facebook and Twitter profiles. By analyzing all the stories available, an overall ranking is calculated and shown on TrendPo's site (www.trendpo.com).
"We started by ranking politicians like fantasy football players because we thought that would be an interesting topic starter," says JD Chang, TrendPo's CEO. "But on November 6th, everything changed for us. It was like a real time favorability poll for every political member, and it correctly called the election."
A week later, Chang had the idea to analyze political issues and expects to predict the outcome of topics like the fiscal cliff, social security, or even people of interest like David Petraeus.
"JD created his own version of text analysis for political news using Whit.li's API (http://developer.whit.li) as a starting point. Can a story have a positive or negative sentiment? Of course, that's expected writer bias. But, JD constructed a way to relate that to political elections. I'm pretty impressed," said Jack Holt, Whit.li's CEO.
But can Chang really predict whether we'll fall off the Fiscal Cliff?
"Right now, Fiscal Cliff averages a TrendPo rank in the 20s. If it hits the top 10, then lawmakers are doing their jobs and people are feeling good. If it drops to 50, then you better call your accountant 'cause you're going to be paying some more taxes soon."
TrendPo is a data metrics company targeted specifically for politicians and political issues. We rank every national politician each day on news, social, and sentiment to show trends and momentum. See the daily rank at www.trendpo.com.
Whit.li's technology provides developers with a way to measure a person's character, interests, and sentiment using text analysis. Whit.li uses its own technology to segment a brand's audience for market research using only its social data. More info at www.whit.li.