A panel of media professionals discussed the various methods for news content personalisation, what their media organisations have achieved with personalisation, and the common challenges related to algorithmic journalism.
To mark the end of the CPN project, we organised a special webinar on how content personalisation can help news publishers create stronger, more engaged relationships with their audience members.
The panellists discussing the theme were:
Swantje Fischenbeck, Innovation Manager at Der Spiegel in Germany
Jarno M. Koponen, Head of AI & Personalization at Yle News Lab in Finland
Gordon Edall, head of labs at the Globe and Mail in Canada
Ine van Zeeland, PHD Researcher on Privacy at imec-SMIT, Vrije Universiteit Brussel in Belgium
The webinar also included presentations from Al Ramich, Founder and CEO of Loomi.AI, and Mattia Fosci, CEO of ID-Ward. The two startups have worked with CPN to develop innovative technical features that support content personalisation – read more about them after the article.
A video recording of the webinar is available below.
Personalisation needs to be combined with testing
As a news publisher, Der Spiegel is at the early stages with its personalisation journey, Fischenbeck said, having started looking into the topic a few months ago. The magazine is investigating questions such as: 1) Can personalisation generate business value while respecting Der Spiegel’s mission as a news publisher? 2) What technical possibilities exist for personalisation, and how can they help in competing for users’ attention? 3) What type of personalisation should Der Spiegel should adopt, and what variables should it be based on: content, time, mood, context, etc.
Fischenbeck emphasised that when determining the right personalisation approach for your publication, it is important to know your content and audience: “We realised that personalisation doesn’t work if you don’t match your solution with your context, company and users.”
At the other end of the personalisation spectrum is the Globe and Mail, which started working on personalised content seven years ago. During this time, the publisher has built a rich recommendation architecture that uses a number of modules to produce recommendations under different conditions.
One particularly successful personalisation feature that has been “In case you missed it”, which highlights articles that the user probably didn’t see but is likely to be interested in. But that was a fairly simple solution to construct, Edall said, adding that many questions related to personalisation are much harder to answer, such as how to make recommendations when you don’t yet know anything about a user – the so-called “cold start” problem.
“As you layer personalisation technologies in, you should also be layering in test-and-learn systems, and learn whether your recommendation engines are working,” Edall said. “It’s not enough to do personalisation, you also have to do testing. It is hard to make salient recommendations, and the only way to know if you’re making salient recommendations is to figure out how to test those recommendations.”
Testing also helps in gathering the kind of proof that may be useful in internal conversations. “As you go to higher degrees of personalisation, it becomes harder and harder for editors to trust it,” Edall said “So learn to talk to the newsroom through data, testing, through evidence.”
A change of mindset
As publishers acquire more and more data about their readers in order to offer personalised content, users are understandably asking how their data is being used. To counter any fears, van Zeeland encouraged publishers to be transparent about the collection and use of user data.
“It’s very important to check what your users want and expect from you. Any type of personalisation would require that,” she said. “It’s important to regularly verify with users whether what you are doing is what they want and need, and whether they understand what you are doing.”
Fischenbeck pointed out that audiences may have reservations when it comes to personalisation of news, but in other context they have embraced the concept: “People are totally into it when it comes to Netflix or Spotify.”
For a publisher, personalisation can also represent a chance to rethink its relationship with its readers. “Instead of just sending stuff out to the world, it’s an opportunity to become more interactive and really engage with our users,” Fischenbeck said. “That’s an important goal for us, and is closely related to the importance of subscriptions these days.”
Also Yle puts the focus on the user when designing personalisation systems, Koponen said. “Our approach has been, we let the person choose. They can have the total vanilla experience, with no personalised content. Or they can have different levels of personalisation,” he said. “It’s very important the user feels in control.”
Koponen highlighted Yle’s news personalisation feature Voitto, a news assistant that shows recommendations directly on the user’s lock screen. Built by a multidisciplinary team, Voitto learns from the user based on both direct feedback (input from user: “more of this” or “less of this”) and indirect feedback (user behaviour). “We had very good results: of the people who opted in to receive personalised news notifications, 90% decided to keep them on.“
Covid-19 and personalisation
At the Globe and Mail, a big driver behind personalisation efforts is the aim to make sure that the right content finds the right audience, Edall said. “It doesn’t help us to write or spend time on a story that's going to matter to someone if that someone can't find it. That is a real problem with the kind of degree and amount of information that anyone has to process in any given day.”
“How much personalisation is needed to augment the wider editorial mandate that we're trying to establish and drive, is one of those things we talk about all the time,” he said. “We usually try to bake personalisation into widgets that are pretty clearly personalised, and where the nature of that widget is clear.”
The ongoing Covid-19 crisis has provided publishers with an opportunity to learn about news personalisation in these exceptional circumstances, where the great majority of news coverage relates to a single issue. Edall said that the coverage of the pandemic, or health information generally, is not a case where the Globe and Mail uses personalisation. But what often happens is, news about Covid-19 is what draws people in, and then many look for other types of news – and that’s where personalisation can play a role.
“Some people really want to move from the serious Covid stuff to much lighter stuff, horoscopes, entertainment articles. Then there's another subset of users who really prefer to be directed to political, business, or economic coverage that's just tangentially related to the overriding issues that are being caused by COVID,” he said. “You can simply give people better options earlier through personalisation that branches out from that dominant focal area for coverage. For me, that's the most interesting way to use personalisation right now.“
You can engineer your way out of the filter bubble
Koponen underlined the need for editorial judgement to coexist with algorithms: “From the very beginning we thought that our journalistic values need to be encoded into the algorithms,” he said. “The journalists in the newsroom need to be able to override personalised recommendations, if there is something very important happening.”
Yle also excludes some content from personalised recommendations. “If something horrible has happened, like a family has died, we don’t want a person to encounter that in our personalised ‘For You’ experience.”
Finally, Edall discussed the much-feared filter bubbles, and whether personalisation can trap readers in echo chambers. “Is there a real danger that wide-scale deployment of personalisation by a general interest news publisher, say a generic national title, could lead into a filter bubble? My answer is unequivocally no – if the personalisation system is designed well.”
“Personalisation systems don’t always have to cater to things that are closest to the core of the things that you have read. We have a large number of different recommendation modules, and some of those recommendation modules are actually explorers that are designed to avoid filter bubbles,” he said.
In other words, algorithms can be engineered in a way that safeguards against the creation of filter bubbles. “I would say, the only way you have recommendation systems that lead to filter bubbles is if you have irresponsible engineers who design the systems that create them.”
