Beating the Algorithm

Image by MUMA Monash

In the old days of “influencer relations” (you know way back when in 2009), PR professionals targeted the magic middle and top tier bloggers, which triggered larger blog coverage, and then more often than not traditional news media.

Since then digital media companies straddled the space occupied by both traditional journals and the top tier of bloggers. They use algorithms to detect hot news stories before they trend in the blogosphere, then break the news before traditional players and bloggers alike.

Specifically, Mashable, the Huffington Post, Forbes, Google and the others use algorithms listen to chatter on the social web. When hot trends bubble up they source the content provider, assign a reporter, or in the worst cases use narrative science — computer-based news writing — to break the story first.

This effectively takes power away from PR executives to affect the news cycle through traditional influencer outreach, and in turn, empowers the crowd to determine stories.

Some news outlets use the crowd to validate top stories, too. Validation is embodied by shares on social networks and comments.

For example, USA Today features stories on its web properties based on the posts that get shared the most. The old assignment editor loses weight in these scenarios.

Some quality publications still offer their own editorial direction into content. For example, CNN uses iReport to harness crowd driven news. Editors analyze bubbling stories, vet the stories that may be featured on their various channels, and assist the stories with more quality-based journalism. Of course as the Boston Marathon Bommbing story showed us, CNN isn’t what it used to be.

The More Things Change…


If you analyze the formula the game may have changed, but it’s still beatable.

Specifically, if news depends on chatter detected by the algorithm, then word of mouth marketers and public relations pros need to develop stories the crowd will embrace and discuss before the news cycle picks it up. This isn’t very different than building a story that a publication’s readers would enjoy.

There are two critical components to beating the algorithm: Creating the story/talkworthy moment, and feeding the crowd so it embraces it. This is an adaptation from David Sifry’s original magic middle formula. Instead of targeting journalists or middle tier bloggers, one positions a story for social network or specific crowd-sourcing pools.

One way of creating talk worthy moments is to create content — e.g. photos, video, info graphic or another form of media — that people go bonkers over. You can even play the algorithm game yourself using tools like TrendSpottr and Bottlenose.

Grumpy Cat is a great example of this, a story that would not see the light of day in the old editorial world. What the crowd wants, the crowd gets.

In 2010, during the Citizen Gulf efforts we were featured twice on the front page of CNN using photographs taken down in the Gulf to expose the Deep Horizon’s impact on fisherman. We used the iReporter platform to host the content, then tweeted and shared the content out to trigger enough views, which in turn, helped trigger editorial coverage.

There was also an element of newsjacking to our approach. CNN covered the ongoing oil spill story, so we simply provided a new wrinkle. But I think this is simply crafting a talk-worthy story. People weren’t discussing the impact on the environment and fishing sector, and that was a huge issue.

By the way, if content isn’t your game, a primary source of social network chatter remains bloggers, specifically independent ones. Breaking a story through the magic middle is a relevant means of driving chatter to trigger an algorithm, but the end game is different. You want conversation in the aggregate to trigger a groundswell, as opposed to getting big bloggers to talk bout you. These two outcomes may be complimentary.

What do you think of algorithm driven news?