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Posts Tagged ‘twitter academy awards’

Jennifer Lawrence, Brad Pitt, Gravity And THAT Selfie – Twitter’s Reaction To The Oscars [INFOGRAPHIC]

Jennifer Lawrence, Brad Pitt, Gravity And THAT Selfie - Twitter's Reaction To The Oscars [INFOGRAPHIC]

What was your best memory of the Oscars? And did you talk about it live on Twitter?

If so, you’re far from alone. More than 14.7 million tweets about the 86th Academy Awards were shared on Twitter during the Oscars telecast, with conversation buzzing around host Ellen Degeneres (and THAT selfie), nominees Jennifer Lawrence and Brad Pitt, Gravity, Frozen and 12 Years A Slave.

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Tweets About The Oscars Were Seen 3.3 Billion Times Worldwide [STATS]

Tweets About The Oscars Were Seen 3.3 Billion Times Worldwide [STATS]

The 86th Academy Awards was, by all accounts, a major success, picking up its biggest television audience in a decade and generating a serious amount of buzz across social media – notably Twitter, where a celebrity-packed selfie tweet quickly became the most retweeted tweet of all time.

Indeed, the chatter was so significant on Twitter that tweets about the Oscars were viewed over 3.3 billion times worldwide.

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The Oscars On Twitter: 14.7 Million Tweets, 254,644 TPS Peak, Most Retweeted Tweet Ever [STATS]

The Oscars On Twitter: 14.7 Million Tweets, 254,644 TPS Peak, Most Retweeted Tweet Ever [STATS]

Yesterday stars and luminaries from the world of cinema gathered together at the 86th Academy Awards to honour the actors, movies and technical achievements in film in 2013, and Twitter was there to reap the spoils.

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Which Tweet Won The Social Academy Awards? [INFOGRAPHIC]

Yesterday we took a look at the the reaction to the Academy Awards on Twitter, with two differing accounts tracking the impact that the Oscars made on the network.

Now, a new analysis has identified the single most popular tweet sent out during the Oscars, and not only was it from a non-celebrity account, but it was about a film that didn’t even win a single award.

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Can Twitter Predict The Oscar Winners?

In a word: no.

TweetReach, a reach analysis service that I like and blogged about here, have been tracking tweets about the Academy Awards for the past month, and have crunched that data into a report that shows exactly who the Twitter collective predicts to win.

In that time, 170 thousand people have tweeted more than 313,000 times about the Oscars, reaching 53.5 million unique Twitter accounts and generating more than 720 million impressions.

So, here are our final Academy Award winner predictions, based on the cumulative unique reach of the nominees.

Best Supporting Actress: Hailee Steinfeld (True Grit)
Best Supporting Actor: Geoffrey Rush (The King’s Speech)
Best Actress: Natalie Portman (Black Swan)
Best Actor: Colin Firth (The King’s Speech)
Best Picture: Black Swan The King’s Speech

Sounds good. But here’s the problem: users on Twitter have absolutely zero influence on how the Academy Award winners are picked. This isn’t the People’s Choice Awards. Oscar winners are voted for and determined by the Academy themselves.

So, unless the 5,835 members of the Academy of Motion Picture Arts and Sciences (AMPAS) have been tweeting constantly about their exact picks, it doesn’t make any difference what Twitter thinks. It’s like asking 100 random people in the street for the winner of the Kentucky Derby, and betting accordingly. Sure, you might get lucky, but that’s all it will be – luck.

Twitter can be a great predictor of many things, especially where sentiment plays a major role in deciding the outcome of an event that is shaped by the public. For example, the winner of American Idol, or even who is most likely to be the next occupant of the White House.

What Twitter can’t do is predict the outcome of an event in which the people polled have no control or influence over whatsoever.

If Twitter’s collective does get the Oscar winners right it will simply be a coincidence. At best an educated guess. And as much as it might seem that I’m being a nitpicker extraordinaire, by any measure that’s quite a bit different to a prediction.