The VMAs, Lady Gaga and Data Science

Hi everyone. I’m the new Data Scientist here at Gnip. I’ll be analyzing the fascinating data that we have coming from all of our varied social data streams to pull out the stories, both impactful and trivial, that are flowing through social media conversations. I’m still getting up-to-speed but wanted to share one of the first social events that I’ve dug into, the 2011 MTV Video Music Awards.

Check out the info below and let me know in the comments what you think and what you’d like to see more of.  And now, on with the show…

3.6M Tweets Mention “VMA”

The volume of tweets containing “VMA” rose steadily from a few hours before the VMA pre-show was broadcast, up to the starting of the pre-show at 8:00 PM ET (00:00 GMT) and remained fairly strong during the event. It trailed to low volume within the hour after the VMA broadcast ended at 11:15 PM ET (03:15 GMT). Tweets mentioning “VMA” totaled 3.6M during the 7 hours surrounding and including the VMA broadcast.

 

Lady Gaga Steals the “Tweet” Show

The largest volume of tweets for an individual artist are the mentions of “gaga.” Lady Gaga performed early in the show and the surge of tweets during her performance surpassed 35k tweets per minute for about 8 minutes. Again in the second half, Lady Gaga tweet volume briefly jumped above 50k per minute. Tweets mentioning “gaga” totaled 1.8M during the 7 hours surrounding and including the VMA broadcast.

As you can see in the chart below, other artists that garnered significant tweet volumes included Beyonce’, Justin Beiber, Chris Brown, Katy Perry and Kanye West. Perry, West and Brown got a lot of attention during their appearances, while Justin Bieber and Lady Gaga lead the counts in volume by maintaining a fairly steady stream of tweets during the broadcast.

Term Representation of Tweets Sampled
VMA 44 %
Lady Gaga 21 %
Beyonce 16 %
Justin Bieber 10 %
MTV 9.2 %
Chris Brown 8.0 %
Katy Perry 5.6 %
Kanye West 4.8 %
Jonas 3.5 %
Taylor Swift 2.1 %
Rihanna 1.1 %
Eminem 0.55 %
Michael Jackson 0.18 %
Ke$ha 0.17 %
Cher 0.14 %
Paramore 0.12 %

 

 

 

Contrasting, it is interesting to note that Beyonce’ and Chris Brown gained most of their tweet attention around their performances with very larger surges in tweet volume. Beyonce’s volume–another Beyonce’ bump–continues after her performance as twitter users absorb the news of her pregnancy.

 

 

One surprise that emerges from looking for other artists connected to the VMAs was Michael Jackson’s tweet volume. While Jackson gleaned many Retweets after winning the King of the VMA poll, he also received a large number of natural tweets lamenting his passing and celebrating his past successes.

Methodology

The free-form text and limited length of twitter messages creates a number of challenges for monitoring an event via twitter comments. People refer to the event differently and focus on different parts of the event. There will be spelling variations and differences in idioms and nicknames used to describe people and performances. Do we search for “Bieber”,”Beiber” and “Justin”?  Will tweeters use “Beyonce” or Beyonce’”? Knowledge of what we are monitoring is required; preparing tools to adapt things we learn during the events is also essential to getting good results.

One effective strategy is to use one or two tokens to identify tweets related to the event. The objective is to choose terms that we know are related to the event, that won’t be widely used outside the event, and that will give a representative sample–diverse and with sufficient volume. Once we have started to collect the event-focused twitter sample, we can look for relevant terms correlated with the filter term to find out what else people are tweeting about during the event.

Hope you enjoyed this first post. Look for more to come.