Beating the Algorithm

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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.
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