I wonder, using big data and predictive analytic, can we predict the winner of x-factor or American Idols from the start of their audition performance? I think we might have a good chance to predict the winner right away.

What if we could only have the information from their first performance, what should be the variables to be used in the predictive model? Here’s from what I could think of:

• The voice: quantified timbre, energy and rhythm
• Song selection: how popular the song was, type of music (pop/jazz/country)
• The singer appearance: body mass, hair color, skin color, clothing, type of shoes, color contrast, etc (some of these variables might not be legal to use)
• The early response from panel of judges: number of yes/no
• Wisdom of the crowds: mentions at twitter, number goods vs bad sentiments, number of videos uploaded to YouTube, number of download from iTunes, etc.
• Audience claps: number of decibels from audience claps

Once we have all of these variables, we might be able to predict the winner this coming season X-factor/American Idols/The voice.

However, if the model is able to predict the winner, who should be benefited from this algorithm? The producer of the show could be one. Once he/she knows who should be the winner, he/she can play with the TV viewers’ emotions by altering some of the significant variables. The audience could be more attached if their favorite singer is about to lose and need more support. With more viewer’s getting more attached, the TV can have higher rating and higher advertising income. Hear the KA-CHING?

Can we do this project just for fun? :)

Predicting the reality show winner using big data