1. Monitoring Real Time Market Sentiment During the Academy Awards Through Twitter

2. Temporal animation Pivot across variables Live filtering Sentiment over time On click geographic details

3. Each Tweet’s sentiment is calculated between +1 and -1 then the total sentiment for the movie is calculated for before, during and after the Oscars. The larger the number to greater the positive (+) or negative (-) sentiment for the movie. The score is indicative of both overall sentiment as well as the volume of people expressing the sentiment

4. Heavy Negative Sentiment for “Black Swan”

5. Heavy Positive Sentiment for “True Grit”

6. Mixed Sentiment for “127 Hours”

7. Each Tweet’s sentiment is calculated between +1 and -1 then the total sentiment for the actor/actress is calculated for before, during and after the Oscars. The larger the number to greater the positive (+) or negative (-) sentiment for the actor/actress. The score is indicative of both overall sentiment as well as the volume of people expressing the sentiment

8. Largely Positive Sentiment for “Jeff Bridges”

9. Largely Negative Sentiment for “Nichole Kidman”

10. Mixed Sentiment for “James Franco”

11. Black Swan Negative Sentiment for Black Swan but Positive Sentiment for its Actress “Natalie Portman” Natalie Portman

12. Reaction to The Social Network Winning Best Score

13. The Reaction to “The Fighter” in the Boston Market