As any self-respecting nerd and Batman lover, I have been eagerly awaiting news on Warner Bros’ next chapter on the Gotham City hero. From theirFacebook page, the studio announced last week that Ben Affleck will be the next Caped Crusader in the anticipated “The Man of Steel” sequel. , most of which was negative, flooding feeds with thoughts on the #batfleck choice. Anyone visiting Twitter over the weekend was sure to have been bombarded with memes, frustrated tweets, and news agencies’ take on the overwhelming public response. io9, a popular blog on science, science-fiction, and the future, quickly responded with their “50 Greatest Tweets about Ben Affleck’s casting as Batman.” There has even been a petition on Change.org with 75,000 signatures!
I am not going to begin to argue as to whether or not Ben Affleck was the right choice for the character; I will leave that to the movie buffs and entertainment critics. However, it is important to see the power of word-of-mouse, the speed at which information travels and the importance of sentiment analysis. I see, as I am sure the people at Warner’s do, the wealth of data to be gleaned from this reaction. How many people visited WarnerBros.com after the press release? How many times has #batfleck been used? Were those comments positive or negative?
How should the movie studio respond? That, I cannot say. Today’s world demands fast immediate results and just as fast response to discontent. So, the question is how do you collect this amount of data, at this speed, and process it into something useful and what information should be gathered? Big Data is not just a buzz word but it will be if companies are not equipped with the right tools to employ the data. It will be interesting to see how Warner Bros uses the information in their future marketing and campaigns for the film.
How do you analyze sentiment?
Blogg by Cathy Andresson
@middlecon_ab
