Kate Gosselin on Dancing with the Stars Photo Credit: ABC

Can Social Media be used to predict the outcome of Reality TV shows such as American Idol and Dancing with the Stars?  We created Reality Buzz based on our real-time automated web data collection platform to find out.

Jennifer Zaino over at Semantic Web wrote a nice article that captures the essence of Reality Buzz and our process of using real-time social media web data to build intelligence in to predictive analytics:  Taking Sentiment Analysis to Dancing with the Stars and American Idol

Check it out.  And if you have the need to automate the access, collection, harvesting, scrubbing, grabbing or scraping or real-time web data to improve market or competitive analysis to improve your strategic decision making, we’re here to help.

By:  Rick Kawamura

Can oddball metrics from Craigslist apartment listings, Subway ridership tallies, Broadway ticket sales, city parking garage count of empty stalls, cardboard box production, or diesel fuel consumption be better economic predictors than traditional, months old government reports from the labor department?  Absolutely!

The Wall Street Journal just published “New Ways to Read Economy – Experts Scour Oddball Data to Help See Trends Before Official Information Is Available” where author Cari Tuna provides numerous examples of Economists around the country using non-traditional methods to better predict economic trends and direction.

The reason for this trend is that traditional reports and data are out of date and often not very accurate.  Who has six months to wait for a government report to make a decision?

Enter Web Data Services

What would make these oddball metrics more valuable and accurate?  Automating the collection process over multiple sources of data and loading it in to the database or BI tool of your choice.

Imagine you had the ability to automate the monitoring of hundreds of sources of data in real time and could react to changes overnight?  What data would you monitor?

Interest rates?  Gold Prices?  Credit Score reports?  Salesforce data?  Apartment listings?  Competitor’s pricing?  Product Buzz?  Customer complaints?  Financial transactions?  Bank balances?  Twitter?  Facebook?  Google Trends?  Linkedin profiles?  Partner inventory?  Shipment dates?

If you can see it in a web browser, whether on the public web, behind a login screen, or behind your firewall, that data can be accessed with Web Data Services to provide you with improved predictive analytics and strategic decision making.

As a fun example, Reality Buzz uses Kapow’s Web Data Server to monitor popular social media sites to evaluate America’s sentiment towards contestants on American Idol and Dancing with the Stars.  Overnight, data is collected and evaluated, and predictions are made about the fate of the contestants before the elimination show the following night.

Hundreds of businesses incorporate Kapow’s Web Data Server solutions to improve competitiveness, product offerings, and strategic decision making.  You can too.  What are you waiting for?

By:  Rick Kawamura

While web data, especially social media data, grows exponentially, the vast array of opportunities for using real-time web data to improve analysis and decision making is limited only by your imagination.  These days, companies must incorporate Web data into their intelligence and analysis tools in order to compete. In some industries it’s a matter of survival.

Real-time data is where the answers are.  It’s where market and customer trends are immediately identifiable.  It’s where deals will be won and where winners will claim their trophies.

Reality Buzz

We recently built something 30M Americans can relate to – a way to predict American Idol and other reality show results based on data harvested from popular social media sites.

Every week on American Idol, contestants perform, their fans dial-in their support for their favorites, and the next day contestants are voted off the show.  During the performances, and for several hours after, fans tweet about and discuss their favorites online, showing support for the ones they want to see voted through to the next show.

We scrape thousands of pieces of web data from twitter, Facebook, forums and discussion sites around the web, apply sentiment analysis, analyze the data, and make predictions about the person(s) to be eliminated from the show, all in the span of a few hours.

We built the robots (automated web data collection processes) in a matter of hours.  Now they are automated to collect the data, transform unstructured data into structured data, and load it into a MySQL database.

In the last two weeks starting with the top 12 contestants, we’ve successfully predicted the American Idol contestant to be eliminated hours before the elimination show aired.  For more information on our latest predictions and to learn more, please visit Reality Buzz on Facebook.

Imagine what you could do for your business with Kapow’s Web Data Server and a few hours creating Kapow robots.  Real-time web data can fuel predictive analytics capabilities to give your company an unfair advantage.

Over 400 Kapow customers are jumping in with both feet.  What’s stopping you?  Learn more on our Kapowtech.com website, or contact us for a Free Trial of the Kapow Web Data Server.

By:  Rick Kawamura