July 28, 2017
3 essential elements to tackle fake news in programmatic

3 essential elements to tackle fake news in programmatic

Earlier this year, IAB Chief Randall Rothenberg called on the industry to address fake news. In response, Google and others have taken measures to remove questionable publications from their networks, but was it enough?

Obviously, abandoning automation isn’t the answer to the challenge of fake news. Getting smarter in its understanding of digital content, and greater transparency about where ads are placed, are essential steps. Here’s what else programmatic can do:

1. Separate the fun from the fiction

Programmatic requires clear rules and standard definitions, which are currently lacking in the field of fake news. Fake news is “news” that is entirely made-up with the intention of deceiving readers. These should not be confused with satirical content that is explicitly fabricated and designed to entertain or illustrate a particular viewpoint.

2. Comprehend the context of content

The industry must also be able to differentiate between outright lies and personal opinions – however strongly expressed. Just because President Trump recently accused CNN of reporting fake news, this doesn’t mean the network is busy concocting wholly fictional news stories to drive ad revenue.

The primitive brand safety tactics that many are using such as blacklists or basic keyword analysis are far from foolproof. Rather than relying on these flawed techniques, semantic analysis technologies such as Natural Language Processing can be used to read digital content just as humans do naturally, allowing automatic filtering of extreme hate or hyper-partisan content. Semantic analysis provides deep insight into the context and sentiment of content, as well as the emotions it evokes, and enables brands to avoid content that does not resonate with their messaging – fake or not.

3. Maintain the human element

While the definition of fake news remains subjective, it will never be possible for automated technologies to be 100% effective in detecting and preventing advertising being served alongside it – some content will always slip through the net. Continuous human verification is necessary to prevent messages from being proactively placed away from such content.

By combining automated semantic technologies with the natural human ability to determine whether content is trustworthy and objective, the industry can begin to rebuild brand trust in programmatic.

While standards are being established to better define issues such as fake news and brand safety, the industry must embrace a combination of cognitive semantic analysis and human review to increase transparency and ensure programmatic ads are always alongside appropriate, authentic content.

Learn more in the full article, Fake News: Another Symptom of Programmatic’s Colossal Rise in MarTechSeries.