UPDATED 10:10 EDT / JANUARY 23 2014

NEWS

Big Data predicts this year’s GRAMMY winners

The GRAMMYs are just a few days away. The music world’s biggest awards show will be held on Sunday, January 26, 2014, in LA. Music lovers will be tuning in on CBS for the live telecast, and I’m pretty sure many SiliconANGLE readers will be rooting for their favorite bands or artists to get that coveted golden gramophone.

As always before major awards ceremonies and events, people just love to try and guess the winners. Today, the music service Spotify has released its own 2014 GRAMMY predictions. Using streaming data, it did rather well in predicting some of last year’s winners, including Gotye’s “Somebody That I Used to Know” for ‘Record of the Year’, and Mumford & Sons’ “Babel” for the ‘Album of the Year’ title.  If Spotify gets its data right again, then the following list could well be an early look at this year’s winners too:

Predicted winners by GRAMMY category, in order of most to least streams on Spotify

Record of the Year

1.    Radioactive, Imagine Dragons – one-third more streaming than BLurred Lines

2.    Blurred Lines, Robin Thicke feat. T.I. and Pharrell

3.    Locked out of Heaven, Bruno Mars

4.    Royals, Lorde

5.    Get Lucky, Daft Punk Feat. Pharrell Williams & Nile Rodgers

Album of the Year

1.    The Heist, Macklemore & Ryan Lewis –  40 percent more streams than Daft Punk’s Random Access Memories, and more than three times as many as the other three nominees combined.

2.    Random Access Memories, Daft Punk

3.    Good Kid, M.A.A.D. City, Kendrick Lamar

4.    Red, Taylor Swift

5.    The Blessed Unrest, Sara Bareilles

Best New Artist

1.    Macklemore & Ryan Lewis – beat Kendrick Lamar by 70 percent and fellow newcomer Ed Sheeran by nearly triple the number of streams.

2.    Kendrick Lamar

3.    Ed Sheeran

4.    James Blake

5.    Kacey Musgraves

Best Pop Solo Performance

1.    Royals, Lorde

2.    Mirrors, Justin Timberlake

3.    Roar, Katy Perry

4.    When I Was Your Man, Bruno Mars

5.    Brave, Sara Bareilles

Best Pop Duo/Group Performance

1.    Get Lucky, Daft Punk Feat. Pharrell Williams & Nile Rodgers –  20 percent more streams than Blurred Lines

2.    Blurred Lines, Robin Thicke feat. T.I. and Pharrell

3.    Just Give Me a Reason, Pink feat. Nate Ruess

4.    Suit & Tie, Justin Timberlake & Jay-Z

5.    Stay, Rihanna feat. Mikky Ekko

Spotify isn’t the only with its predictions however…

Based on searches made with Bing in 2013, the Record of the Year will go to Blurred Lines, whilst either Katy Perry or Justin Timberlake will win Best Pop Solo Performance, and Taylor Swift will bag this year’s Best Album of the Year award. Though Spotify and Bing disagreed on most predictions, they did agree on one thing, Macklemore and Ryan Lewis will win Best New Artist this year.

Shazam, the mobile phone-based music identification service, also released its own predictions based on its users listening habits. With 5.4 million Shazams, it predicts that Blurred Lines will be named Record of the Year, The Heist as Album of the Year with 11.4 million Shazams, Just Give Me a Reason by Pink as Song of the Year with 4.3 million Shazams, and like the other predictions, Macklemore and Ryan Lewis will be named as Best New Artist.

And CivicScience and AXS TV are teaming up to deliver predictions in their GRAMMY Prediction Special, which airs today, January 22 at 8 p.m. ET (5 p.m. PT).

“With this special we are bringing the world of analytics to music in a new fashion, striving to address an area that is seldom tackled, which is correctly predicting winners before the envelopes are opened,” stated Mark Cuban, AXS TV founder and member of CivicScience’s Advisory Board.

“Partnering with CivicScience—led by John Dick, who will be appearing on the show—it is our goal with AXS TV’s GRAMMY PREDICTION SPECIAL, to use CivicScience’s advance polling, analytics and analysis to gauge who the front runners are on this monumental night.”

CivicScience is using a proprietary method for predicting the Grammy winners, by analyzing results to surveys conducted online among a mix of music enthusiasts and general consumers.


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