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Oscar twitter geo_sentiment

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Transcript

  • 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