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to cover in the first place. The Huffington Post, for example, relies on thousands of unpaid bloggers who contribute content either out of passion for the topic they write about or else to benefit from the visibility they receive from being published on a widely read news site. Other sites, like Examiner.com, meanwhile, retain armies of contributors to write about specific topics of interest to them, and pay them by the page view. And finally, sites like Yahoo!’s news blog “The Upshot” and Associated Content not only crowdsource the writing work but also track search queries and other indicators of current crowd interest to decide which topics to write about.7

The idea of measuring audience interest and reacting to it in close to real time has also started to gain traction beyond the revenue-challenged world of news media. For example, the cable channel Bravo regularly spins off new reality TV shows from its existing shows by tracking online buzz surrounding different characters. The shows can be launched quickly and at relatively low cost—and if they don’t perform, the channel can quickly pull the plug. Following a similar principle, Cheezburger Network—a collection of nearly fifty websites featuring goofy user-contributed photos and videos, most with funny captions—is capable of launching a site within a week of noticing a new trend, and kills unsuccessful sites just as quickly. And BuzzFeed—a platform for launching “contagious media”—keeps track of hundreds of potential hits and only promotes those that are already generating enthusiastic responses from users.8

As creative as they are, these examples of crowdsourcing work best for media sites that already attract millions of visitors, and so automatically generate real-time information about what people like or don’t like. So if you’re not Bravo or Cheezburger or BuzzFeed—if you’re just some boring company that makes widgets or greeting cards or whatnot—how can you tap into the power of the crowd? Fortunately, crowdsourcing services like Amazon’s Mechanical Turk (which Winter Mason and I used to run our experiments on pay and performance that I discussed in Chapter 2) can also be used to perform fast and inexpensive market research. Unsure what to call your next book? Rather than tossing around ideas with your editor, you can run a quick poll on Mechanical Turk and get a thousand opinions in a matter of hours, for about $10—or better yet, have the “turkers” come up with the suggestions as well as voting on them. Looking to get feedback on some design choices for a new product or advertising campaign? Throw the images up on Mechanical Turk and have users vote. Want an independent evaluation of your search engine results? Strip off the labels and throw your results up on Mechanical Turk next to your competitors’, and let real Web users decide. Wondering if the media is biased against your candidate? Scrape several hundred news stories off the Web and have the turkers read them and rate them for positive or negative sentiment—all over a weekend.9

Clearly Mechanical Turk, along with other potential crowdsourcing solutions, comes with some limitations—most obviously the representativeness and reliability of the turkers. To many people it seems strange that anyone would work for pennies on mundane tasks, and therefore one might suspect either that the turkers are not representative of the general population or else that they do not take the work seriously. These are certainly valid concerns, but as the Mechanical Turk community matures, and as researchers learn more about it, the problems seem increasingly manageable. Turkers, for example, are far more diverse and representative than researchers initially suspected, and several recent studies have shown that they exhibit comparable reliability to “expert” workers. Finally, even where their reliability is poor—which sometimes it is—it can often be boosted through simple techniques, like soliciting independent ratings for every piece of content from several different turkers and taking the majority or the average score.10