Determining The Peoples Oscars

Like previous social sentiment analyses on the Super Bowl, World Series, film and retail, IBM and USC’s Annenberg Innovation Lab conducted an analysis of the Twitterverse to determine the “The People’s Oscars.” The Academy Award project was done in partnership with the Los Angeles Times and demonstrated how applying analytics to big data could be the next game-changer for Hollywood and how these tools are transforming journalism.

New analytics technologies and advances in natural language processing make it possible to understand positive, negative and neutral sentiments; distinguish irony; and even apply “machine learning” to figure out which tweets are just background noise and which are truly important. Through analytics, users can glean actionable insight from what the public is saying through social media outlets and can then respond to and engage with their key stakeholders in a way that wasn’t possible before.

By analyzing the number of tweets-and the positive or negative nature of the tweets-a movie or person receives, USC students were able to predict who “the people” thought should win the Academy Awards for Best Actress, Best Actor and Best Picture. You can see all the results, and how the “people’s choice” changed over time, here.

Meryl Streep’s performance as Margaret Thatcher generated more buzz in the Twitterverse than any of the other nominated leading ladies by a large margin. The Academy agreed, giving Streep her third gold statue.

George Clooney received more than 1,100 tweets, nearly four times more than eventual award winner Jean Dujardin. While the Academy rewarded “The Artist” actor, the people preferred Clooney’s performance in “The Descendants.”

“The Artist” may have taken home the grand prize at the Academy Awards, but “Hugo” received nearly double the amount of tweets. However, the 2,790 tweets for “Hugo” had a more negative tone than the 1,888 for “The Artist,” perhaps foreshadowing the latter’s victory.

IBM’s collaboration with USC is much more than an analysis of fan favorites-it’s an example of how organizations can better understand their audience preferences about products and services and use social media to improve those products, services, marketing and branding efforts. In the case of the Oscar initiative, the project demonstrated how movie studios can use data to improve box office results. Applying analytics to big data shows the powerful influence social media users can have on organizations, and how social media data can impact the bottom line for businesses of all sizes in all industries.