What can journalism learn from I Can Has Cheezburger?

Editor’s Note: This is the second of two guest posts by Scott Porad, who is part of the team behind I Can Has Cheezburger? and the Cheezburger Network, the leading online destination for user-generated humor and entertainment content.

Previously I addressed the misconception that user-generated content is free. To make user-generated content work, Cheezburger expends significant cost to sift through all the user submissions to find the best quality content. However, including this expense, content costs us less to acquire and is undoubtedly of higher quality. This fundamental win-win is the promise of crowd-sourcing and user-generated content.

With that in mind, what can news journalism learn from I Can Has Cheezburger? There are probably many lessons, but one that stands out to me is a fundamental shift in the concept of reporting from “sourcing” toward “filtering.”

As an outsider, someone who never has worked as a professional news reporter, it seems that in the pre-Internet era the primary constraint on a journalist was a lack of sources with quality information. That is, in order to know what was happening somewhere, you had to know someone there who could be a source. After finding a source, a reporter would verify the quality of their information, typically by corroborating it with additional sources. In short, the name of the game was finding and developing sources.

Today, the problem is the opposite: a journalist has a million sources–anyone with e-mail, a cellphone camera, a blog or a Twitter account is a potential source. The issue now is not finding sources, but figuring out who among the myriad of them is actually providing the right information.

By way of example, let’s refer to the recent “man overboard” report on a Washington State Ferry. Within moments, Twitter was alive with real-time reports. All the news reporters had a million sources, including the US Coast Guard which was tweeting events as they happened.

But that didn’t mean they were all quality sources: yes, a report was made, helicopters were dispatched, and a search was on. But, there was no man overboard; it was a false alarm. Suddenly, the job of the news reporter changed; no longer was it “where or how can I find someone who will tell me what’s going on aboard the ferry?” Now it was: “of all these people reporting what’s happening on the ferry, who is telling the truth?”

Earlier this year I was at a panel discussion that included two leading online technology reporters: Louis Grey of louisgrey.com and Marshall Kirkpartick of ReadWriteWeb.com. Each reporter discussed the tools and techniques they used to sift through the endless volumes of sources online in order to reveal the right stories to be reporting.

I was struck as Kirkpatrick described how, at considerable and non-trivial expense, ReadWriteWeb analyzes their sources to understand which of them are the best. Like Cheezburger does with moderating images and video, ReadWriteWeb performed this analysis using a human-based process–it was not automated with computers. And, like Cheezburger, the name of the game for ReadWriteWeb is being able to effectively sift through the noise to find the signal, in a word: filtering.

And, a final example to illustrate the importance of filtering, from beyond the media world and into e-commerce: Amazon.com has relied on user-generated content since day one with their Customer Reviews. However, popular titles often have thousands of reviews submitted. For example the most recent Harry Potter book currently has 3,328 user-submitted reviews. Each of these reviews is reviewed by an Amazon employee for spam, language, appropriateness, etc.

The problem for Amazon, like Cheezburger and ReadWriteWeb, is not an issue of having enough content, but rather an issue of filtering out the best. Like Cheezburger, they have solved this problem through a combination of employee and user moderation. Leading usability expert Jared Spool estimates the solution has been worth $2.7 billion to the company.

Additionally, the reason companies invest in processes that filter for quality is because better content drives growth. Higher quality content equals positive word-of-mouth equals more traffic and users. Of course, more users leads to more submissions leads to better content. The lesson is that content publishers can’t simply publish every piece of user-generated content that is submitted, or it will diminish the quality of the product resulting in the exact opposite effect.

There is still value for news reporters and organizations to be “source leaders.” I am one who believes that there is an important role for the professional news reporter in our society. But it is clear to me that user-generated content or crowd-sourced information is a valuable addition to news journalism because it can yield more and better information, and often faster.

However, as I’ve illustrated, that information comes with a cost which is finding ways to separate the signal from the noise. The task news reporting has shifted toward filtering. My view is that winners in the Internet era of news journalism will be the people and companies who, like Cheezburger, ReadWriteWeb and Amazon, develop systematic ways of filtering the flood of user-generated content and sources down to those with the best content. The result will be higher quality news and information, that is more relevant and on target with the audience, at a lower cost.

Scott Porad is the part of the team behind I Can Has Cheezburger? and the Cheezburger Network, the leading online destination for user-generated humor and entertainment content. Scott writes about web startups, new media and miscelleany at http://scottporad.com, and you can follow him at http://twitter.com/scottporad.

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