Google DNI has announced the results of its 4th round of innovation funding, and Twipe is proud to be among the winners for our collaborative project with The Times and The Sunday Times on ‘JAMES, your digital butler‘.
With over 100 winners, there is a lot of innovation in this group. Here are 8 especially interesting projects, focusing on robot journalism, monetisation and reader engagement.
Business Journalism Robot, Børsen and Lasso (Denmark)
This project creates a robot to write in the journalistic style of Danish business newspaper Børsen. The robot will be used to report financial news faster and more accurate than human reporters can. Not only will the robot write stories itself, it will also provide predictive suggestions to reporters by learning from existing content. It will help to write unlimited numbers of business news stories detached from limitations of human reporters.
Playwall, Golem.De + Computec Media (Denmark)
Golem.De, a German online publication on the IT industry, has a high proportion of readers using ad-blockers. This group has not been able to be monetised yet, even with the offer of an ad-free subscription. The new Playwall will let adblocking readers support Golem.De by completing small tasks, such as data processing or training AI algorithms. In the future, they even envision allowing access in exchange for code debugging tasks.
Not to be confused with Dutch startup, The Playwall, which allows readers to pay for digital content by giving their opinion. (For more on this spin on paywalls, read our interview with Playwall founders in the latest edition of Trends in Digital Publishing.)
News Quality Scoring, Monday Note (France)
In the past, there has been no correlation between the cost and effort put into high-quality journalism and its tangible value. News Quality Scoring seeks to solve this problem, by matching premium advertising with value-added, high-scoring content. This will raise revenue per page for high-quality journalism, as well as benefit paid-for content models, by improving the performance of recommendation engines.
In an interview with Nieman Lab last month, creator Frederic Filloux discussed his project and how it could be used in the future to recommend personalised content to readers.
“Curation is a very important step. It broke my heart to see that since I’ve been in this business, none of the [successful recommendation engines] have been actually produced by existing news organizations. You see a lot of applications doing that for money and so on. You don’t see any great media using their recommendation power — their credibility to put them in a position to recommend.” – Frederic Filloux, News Quality Scoring
Innovative Dynamic Paygate, Neue Zuercher Zeitung (Switzerland)
While many publishers currently have rule-based paygates that show different messages or offers to users, such paygates still require high effort to create all the rules for specific customer journeys. NZZ’s innovative dynamic paygate will be much more scaleable, through the use of algorithms with machine learning capabilities that can test combinations of message, offer, and visualisation to convert potential subscribers.
Spectral, Nuzzera (Germany)
Spectral is an article recommender system that reduces the effects of the ‘filter bubble’. While Spectral uses machine learning to adapt to each reader’s preferences, it also recommends articles that offer new perspectives. Additionally, it can help improve reading ability by offering slightly more difficult articles.
“Our user research has shown that even readers who are aware of their filter bubble cannot consistently escape it in everyday life. That’s why we are working with Spectral on an algorithm that aims to broaden the perspective while providing a positive user experience – after all, reading should be fun.” – Janine Perkuhn, co-founder of Nuzzera
Studio Polaków, Fratia (Poland)
A collaborative effort from journalists in print (wSieci), TV (wPolsce.pl), and online (wPolityce.pl), Studio Polaków will allow readers to chat with the journalists via live video. This project stems from readers expressing a desire to co-create projects. Such a desire from readers is a key indicator of reader engagement, so it is great to see Fratria leveraging it to further engage their readers.
Quantifying Knowledge, Financial Times (UK)
A great example of knowing your readers, the Financial Times will reward its knowledge hungry readers with live ‘knowledge scores’. Their project Quantifying Knowledge will also help guide readers to relevant articles to increase their scores, adding a gamification element to news consumption.
Mooding, Johnston Press (UK)
By harnessing a reader’s state of mind and profiling their affinity to different types and tones of content, Mooding will be able to personalise the reading experience and improve engagement. This is in contrast to the common targeting of readers by geography, demographics, or behaviour. The deeper understanding of readers offered by Mooding will allow better optimisation of content plans, product development, and commercial solutions.
“We’re delighted to receive the support for these projects from Google. With it, Johnston Press has the opportunity to take a another positive step forward in making the most of the data, content and product challenges media owners like ourselves face.” – Steven Thomas, director of emerging products at Johnston Press
Johnston Press also received funding for ‘Local Active‘, a hyperlocal, mobile-focused service to deliver location-based information, deals, and news in this round of funding from Google DNI.