How Data Analytics Drives Media Polarization

Why reliance on data analytics is detrimental to journalistic quality


President Obama last year expressed concern about what he labelled, ‘the balkanization of the media,’ arguing that ‘our media is now splintered. Some people are just watching Fox News; some people are just reading the New York Times. So they don’t even start with a common baseline of facts. They almost occupy two different realities in terms of how they see the world.’

Since he made his speech, things have arguably got worse, driven by the 'fake news' rhetoric that comes out of the White House on a daily basis. Reuters Institute's 2017 Digital News Report found that America’s media environment is more polarized than any other Western country. Two-thirds of conservatives watch Fox News, and an increasing number, 19%, visit the ultra-right wing site This has cultivated an environment in which 51% of left-leaning Americans trust the news and only 20% of conservatives say the same.

It is easy to blame Trump for all of this, but it is not a new problem. One of the most significant contributing factors is actually nothing to do with Trump, and it is one that is completely fixable.

This issue is the move by papers online and the increasing use of data analytics as a tool for driving traffic. Newspapers and other media outlets are now collecting data to an extremely high degree of granularity, all the way from basic metrics such as views, down to how long a user hovers over a particular link before clicking on it. They use this to determine behavioral patterns that can be leveraged to understand everything from the best time to post an article to the style of headline that will gain the most engagement. The primary revenue stream for the majority of online news outlets is advertising, and more traffic means more revenue. Understanding the audience is the best way to get this traffic, and data is the best way understand the audience.

The BBC’s Director of News and Current Affairs, James Harding, wrote in a 2015 report that using data around how content is being consumed effectively will be a key challenge for journalism moving forward. In another recent Reuters Institute survey of industry leaders from across 25 countries, 76% agreed with him, and said it would be vital for understanding and targeting audiences in 2016. The extent to which newspapers online arms are led by this data varies. The Guardian and the Financial Times, for example, consider themselves to be data informed. The FT employs a wide range of ‘audience engagement’ experts who sit alongside traditional editorial staff, including a social media team, engagement editors, a data analyst, a marketing manager, an SEO expert, an engagement strategist who helps structure all the projects with relevant metrics, and a digital editor focused on producing bespoke content specifically for social.

The core aim of the Financial Times’ audience engagement strategy is to expand the reach and impact of FT journalism and drive quality engagement both on and offsite. The Guardian is also now heavily informed by data. It has used its in-house real-time analytics tool, Ophan, since 2012, which provides exceptionally detailed minute-by-minute data on individual articles that can be easily accessed by all employees with a Guardian email address and password. In December 2015, the Guardian reported that more than a thousand employees had used the tool in the previous month. Chris Moran, audience editor at the Guardian, notes that with this information, ‘We can add subheadings, pictures or video and make sure we're selling a piece accurately, but those things don't necessarily have anything to do with the quality of the journalism.’

These are admirable sentiments. And the quality of the Guardian and the Financial Times’s journalism is testament to their skill at using audience data without allowing it to overwhelm editorial priorities. The use of analytics to increase engagement is necessary in the incredibly competitive world of internet news, as even giants of the industry struggle for profitability. However, data-informed journalism is one thing, data-led journalism is quite another, and when it starts to overly influence editorial policy, journalism is in trouble. This is not just a problem of driving traffic for ad revenue, it also gives journalists a direct incentive to write simply with views in mind. Nobody writes an article hoping that nobody will read it, regardless of ad revenue, and many journalists have shown themselves capable of embellishing for readership and awards before the internet and analytics were even thought of. Analytics risks becoming a distraction from real journalism, forcing them to focus overly on what the audience wants to read as opposed to important things that people need to know. It also leads to sensationalist headlines and a reactive model that simply amplifies various prejudices of the audience by continually banging on the same drum and framing stories just to invoke a strong reaction that will keep them engaged and loyal to your brand, because it feels as if they are loyal to you too. Using data to increase audience engagement is indeed a key challenge for journalists, but using it in such a way as to ensure what’s important is still being reported in a responsible manner is of even greater importance.


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