Select your localized edition:

Close ×

More Ways to Connect

Discover one of our 28 local entrepreneurial communities »

Be the first to know as we launch in new countries and markets around the globe.

Interested in bringing MIT Technology Review to your local market?

MIT Technology ReviewMIT Technology Review - logo

 

Unsupported browser: Your browser does not meet modern web standards. See how it scores »

The online social network Twitter has recently gained a reputation for a certain degree of clairvoyance.  

The combined wisdom of the Twitter crowd can predict, among other things, the movement of stock markets, the spread of news and the box office revenues of movies. Or so we’re told.

Today, Felix Ming Fai Wong and pals at Princeton University in New Jersey, pour cold water on the idea that Twitter is a reliable predictor of the future, at least as far as the success of movies is concerned.

During this year’s Oscar season (2 February to 12 March), these guys collected 1.7 million tweets that contained the titles of 34 recently released or Oscar-nominated films. Of these, about half turned out to be irrelevant. (For example, “thanks for the help” does not refer to the movie The Help!) 

They then classified the remainder according to whether they contained positive or negative comments and whether they were tweeted before or after the person had seen the movie, to distinguish between hype and genuine opinion. 

Finally, they collected reviews from the Internet Movie Database and RottenTomatoes.com about the same films

Wong and co then crunched this data to see how reviews on Twitter compare to those from the other online sources.

It turns out that a number of interesting patterns emerge. For example, Twitter users post far more positive reviews than negative ones, which Wong and co say may have implications for marketers.

“Instead of focusing on reducing the negative reviews from a few dissatisfied customers, it may be better to focus on enhancing the already high proportion of positive reviews on online social networks and use virality effects to influence consumers,” they say.

They also found  that Twitter’s predictive ability is limited. For example, the reviews on Twitter do not necessarily reflect the reviews that appear on other online sites.

What’s more, in contrast ot other studies, the Twitter data does not always translate into box office revenue (although in some cases it can). “Marketers need to be careful about drawing conclusions regarding the net box-office outcome for a movie,” conclude Wong and co.

So by this reading, Twitter’s predictive ability seems to have been overhyped, at least as far as box office revenues are concerned. It’ll be interesting to see whether a similar story emerges for other areas such as stockmarkets.

Ref: arxiv.org/abs/1203.4642: Why Watching Movie Tweets Won’t Tell the Whole Story?

6 comments. Share your thoughts »

Tagged: Web

Reprints and Permissions | Send feedback to the editor

From the Archives

Close

Introducing MIT Technology Review Insider.

Already a Magazine subscriber?

You're automatically an Insider. It's easy to activate or upgrade your account.

Activate Your Account

Become an Insider

It's the new way to subscribe. Get even more of the tech news, research, and discoveries you crave.

Sign Up

Learn More

Find out why MIT Technology Review Insider is for you and explore your options.

Show Me