Impact of Twilight on M&E Industry Is More Bigger... It ruled box office and social media - IBM vs. Twilight fans | Robert Pattinson Daily News, Photo, Video & Fan Art |

Reaction of Twilight fans is so emotional that it breaks IBM emotional analytics. The problem with Twilight is, apparently, that it's too emotionally complex. It can be very useful to use its audience reactions as a way of teaching computers how to process emotions.

The final installment of the Twilight Saga series of movies, The Twilight Saga: Breaking Dawn Part 2, didn’t just rule the box office over the Thanksgiving weekend, it also ruled social media, with more than 5 million Tweets devoted to its mix of horror, soap opera and teenage angst. However, the content of those Tweets wasn’t necessarily as straightforward as you might expect, and that complexity caused problems for IBM when it tried to analyze the online chatter.

IBM researchers worked with analysts from USC Annenberg to look at the Twitter commentary on Breaking Dawn Part 2 and other movies in the two weeks leading up to the Thanksgiving weekend with the intent of using the messages to “teach” its computer systems to be able to more easily recognize and process emotional responses. The problem was, Twilight fans were a little bit more emotional than IBM techs had anticipated, and expressed those emotions in a way that made them less easily “read” by automated systems.

According to the write-up in the Hollywood Reporter (, applying “analytics and natural language processing technologies to study the tweets” revealed that “some of the sentiment was reflecting the ‘audiences’ emotional reaction to the tear-jerking moments in the movie.’”

IBM’s general manager for Media and Entertainment, Steve Canepa, says that automating the collation and accurate analysis of audience reaction through social media to an entertainment event is going to become increasingly important to studios and other content creators as Twitter, Facebook and other social outlets allow audiences to share their reactions faster than old-fashioned polling methods can measure. “What we are doing is essentially creating a focus group in real time,” Canepa explained, adding “We are attempting to understand what are they saying, what motivates people to see [a] movie.”

For now, the science of understanding sentiment on Twitter is being highlighted as a potential marketing tool for movie studios and TV networks. But the potential applicability of predictive analytics goes further.

So Twilight and Twihards help to do it better...