Top trending keywords in each 10-minute blog between 11 PM to 2 AM (eastern time). The pink shade is an indication of negative sentiment percentage on a relative scale.

La La Land crew could never have imagined in their wildest dreams that they would end up handing over the best picture award to the cast of Moonlight at Oscars 2017. Be it the best picture fiasco, paying tribute to someone alive in the memoriam, moving acceptance speeches, Academy Awards 2017 was a roller coaster ride. It was probably too much for us humans to digest, so we let our AI algorithms analyse Twitterati’s reactions as the events unfolded. Let’s get started with the ride. Shall we?

oscars 2017
Top trending keywords in each 10-minute blog between 11 PM to 2 AM (eastern time). The pink shade is an indication of negative sentiment percentage on a relative scale.

Before the launch of main proceedings, showstoppers of the red carpet ceremony Leslie Mann, Javier Bardem and Meryl Streep in stunning blue were the most discussed people. The opening monologue by Jimmy Kimmel where he mocked Donald Trump was also trending. Jimmy thanked Mr President for making the Oscars 2017 look less racist. But as the show progressed, there were two major peaks in negative sentiment (~11:25 PM and 12:20 PM) following which it remained elevated for the rest of the show. We dug deeper and analysed the change in underlying emotion during those periods of a spike in negative sentiment.

oscars 2017
Top trending keywords in each 10-minute blog between 11 PM to 2 AM (eastern time). The pink shade is an indication of negative sentiment percentage on a relative scale.

Our AI observed a spike in anger at ~12:20 AM due to the best picture award mix-up (probably the most unforgettable Oscar moment). Award presenters Warren Beatty and Faye Dunaway announced La La Land for the best picture, re-creating a Steve Harvey moment from the Miss Universe title mishap. Soon after that Warren, Faye and (surprisingly) Steve’s names started trending on Twitter along with other related keywords like #bestpicture, ‘wrong envelope’ and ‘holy fuck’. To control the situation, host Jimmy Kimmel joked, “This is unfortunate, I personally blame Steve Harvey for this”. This brought Jimmy in the cross-hairs of the angry Twitterati.

This makes sense but what about the spike in negative sentiment ~11:25 AM? As usual, we let AI do the digging for us.

oscars 2017
Top trending keywords in each 10-minute blog between 11 PM to 2 AM (eastern time). The pink shade is an indication of negative sentiment percentage on a relative scale.

There was a spike in tweets with undertones of sadness during the time of emotionally charged memoriam where the academy paid tribute to the artists the film industry lost in 2016 with Sara Bareilles performing during the segment. Jennifer Aniston paid a teary tribute to Bill Paxton who died just hours before the Oscars 2017. The atmosphere got all clouded with sadness that faded soon enough after another bump in the Oscar ride. Australian producer Jan Chapman’s photo appeared in the memoriam even though she is alive and kicking. This explains the second peak in angry emotions during that time.

Statistically speaking, the odds of two major back-to-back blunders in announcing the grand finale award (Oscar for best film and Miss Universe) are very low, unless they happened by design. We don’t know the truth, but what we do know is that we had a great time analyzing the twitter’s reaction to this roller-coaster ride. We deduced these insights from a sample of 600,000 #Oscars 2017 related tweets without reading any of them. Our AI-based NLP-stack functions as a powerful research tool for brands by giving them unparalleled insights from unstructured data.

AI is now smart enough for understanding text

At Karna-AI, a ParallelDots product, we deploy a range of cutting-edge AI techniques to derive meaningful insights from large chunks of unstructured text. This can be of great use to brands, market research companies and consulting agencies of all kinds. If you have any questions or suggestions, we would love to hear from you. 

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