Application Development: IBM Analytics Power the People's Oscar Picks
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.
George Clooney may not have gone home with an Oscar this year, but he earned "The People's Oscar," based on positive-to-negative sentiment from Twitter according to IBM, USC Annenberg and the Los Angeles Times' Oscar Senti-meter. Developed by the LA Times, IBM and the USC Annenberg Innovation Lab, the Senti-meter combs through and catalogs a high volume of tweets each day and uses language-recognition technology to gauge positive, negative and neutral opinions shared in the messages. Focusing on tweets captured by the Senti-meter about the nominees for Best Picture, Best Actor and Best Actress, it was Meryl Streep, star of "The Iron Lady," who led largest volume and positive sentiment of tweets. Streep garnered more than 200,000 total tweets during the course of the project, indicating that she was by far the most popular topic and beloved actress of the discussion surrounding the Academy Awards. IBM's collaboration with USC and the LA Times on this project is much more than analyzing which best picture or movie star fans are rooting for-it's a real-life example of how movie studios can better understand their audience preferences and use social media to improve their marketing programs and, in turn, improve box office results. It's a way to illustrate the powerful influence social media users can have on organizations, and how social media data can be a powerful tool that impacts the bottom lines for businesses of all sizes in all industries.