Oscar twitter geo_sentiment

Monitoring Real Time Market Sentiment During the Academy Awards Through Twitter

Temporal animation

On click geographic details

Live filtering

Sentiment over time

Pivot across variables

Movie Total Tweets Total Tweets with Geography

Pre Oscar Sentiment

During the Oscars Sentiment

Post Oscar Sentiment

Black Swan 36327 15102 -115.5530427 -906.9070869 -360.2322284

The Fighter 20185 8835 +36.4875626 +1254.759607 +53.12309493

Inception 78332 32905 -3.920558458 +671.1877858 -14.36446767

The Kids Are All Right 1664 831 +15.70406053 +86.07639343 +0.158883083

The Kings Speech 69240 32652 +32.11218158 +1087.142853 +645.1774999

127 Hours 3722 1947 +0.852030264 -26.38629436 -2.306852819

The Social Network 57390 27339 +4.101268236 +930.7190018 -52.24137274

Toy Story 3 57294 23313 +13.09035489 +277.1017582 +226.3850153

True Grit 6315 3484 +183.9611637 +818.0301819 +111.2789299

Winters Bone 3018 1811 +7.465735903 +9.725887222 +0.317766167

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

Heavy Negative Sentiment for “Black Swan”

Heavy Positive Sentiment for “True Grit”

Mixed Sentiment for “127 Hours”

Movie Total Tweets Total Tweets with Geography

Pre Oscar Sentiment

During the Oscars Sentiment

Post Oscar Sentiment

Javier Bardem 8906 4019 1.386294361 19.11218158 6.465735903

Jeff Bridges 7803 4200 5.852030264 154.8350207 54.88477031

Jesse Eisenberg 7095 3655 -6.624618986 -47.80532876 -38.79441542

Colin Firth 38656 18747 23.63553233 467.9956728 240.8647126

James Franco 106296 55653 68.58883083 -62.40586212 -216.5342641

Annette Bening 2805 1513 1 26.9532985 -5.772588722

Nicole Kidman 25345 10890 -4.386294361 -280.2789299 2

Jennifer Lawrence 10358 5188 126.1091335 154.0593839 -7.079441542

Natalie Portman 95628 40151 4.180709778 580.1375463 257.0982201

Michelle Williams 11659 6103 -57.90964511 17.72588722 6.534264097

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

Largely Positive Sentiment for “Jeff Bridges”

Largely Negative Sentiment for “Nichole Kidman”

Mixed Sentiment for “James Franco”

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

Black Swan

Natalie Portman

Reaction to The Social Network Winning Best Score

The Reaction to “The Fighter” in the Boston Market