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Selling News to Audiences – A Qualitative Inquiry into the Emerging Logics of Algorithmic News Personalization in European Quality News Media: Digital Journalism: Vol 0, No 0
How do news organizations design and implement algorithmically personalized news services? We conducted 16 in-depth interviews with professionals working in European public service broadcasting and commercial quality news media to answer this question. The news business is undergoing rapid transformations regarding how news production is financed, how news is produced and delivered to audiences and how citizens consume news. In all of these changes algorithmic recommender systems play a role. We focus on news organizations’ own personalized news services, and analyze how they define the role of personalization in contributing to the financial success of the organization, in reaching and retaining audiences, and in fulfilling their editorial mission. We interviewed editors, journalists, technologists and business intelligence and publishing professionals to gain a structural understanding of the often conflicting goals of personalization. We found that rather than focusing on increasing short-term user engagement, European quality news media try to use news personalization to increase long-term audience loyalty. In distinction to the “platform logic of personalization”, which uses personalization to produce engagement and sell audiences to advertisers, they have developed a “news logic of personalization”, which uses personalization to sell news to audiences.
algorithms  Research  personalisation  t 
3 hours ago by paulbradshaw
Times titles halve digital subscriber churn with tailored emails from AI named 'James' - Press Gazette
The “digital butler” known as James (Journey Automated Messaging for Higher Engagement) creates individualised emails by predicting content that subscribers are likely to be interested in, then sending it in their preferred format at the time they are most likely to read it.
ai  email  t  times  personalisation 
21 days ago by paulbradshaw
What journalists talk about when they talk about AI | Polis
It’s important to keep in mind that human-centred design does not refer to the people in the newsroom only. Our participants showed significant concerns in relation to how we can properly explain AI to the audience and how we can make sure that AI is implemented in a way that is ethical and transparent. How do we make it clear when a machine has contributed to our reporting, or even drafted an entire article? How can we illustrate the process the machine has followed and ensure that it has been designed and trained respecting the rules of journalistic integrity? We also heard that news outlets  are still struggling to understand how much personalisation is too much personalisation. Can we create shared guidelines that could help us to be clear and transparent in regard to what elements have led the algorithms to present the audience with certain content in a certain way?
ai  personalisation  automation 
28 days ago by paulbradshaw
“Local news is all around us: How to turn city streets into a true homepage.”
early signs that location-aware story notifications about topics people are interested in may be up to 4x more engaging than regular news alerts (the sample size is small, and the insights are directional), but we also learned that people may not want to stop to read an entire article while out walking. We learned that new newsroom roles and tools would be needed to support these products at scale, including better location databases, editors for “places” and a revamped CMS
geo  personalisation  location  geotagging 
11 weeks ago by paulbradshaw
Explaining devices that learn: Google AI and IF by María Izquierdo - IF
"If devices present a personalised view on the world, people should be able to understand how and when personalisation happened. But how do you explain that in a way that people can actually digest, especially when it comes to complex scenarios like federated learning? And can you take the leap from explaining what’s happening at certain points, to creating interfaces where people can stop or influence what’s happening? Those are some of the questions we prototyped in this project."
machinelearning  explanations  work  AI  publicservice  personalisation 
12 weeks ago by tristanf
The Dangers of Overpersonalization
In our research, we observed some of the downsides of personalization on the web. In particular, one of the problems with a personalized experience is that users are placed into a niche and start experiencing only information that goes into that niche. However, individuals are often multifaceted and change over time. A system that caters to a single user facet risks becoming boring or even annoying and can miss opportunities.
research  personalisation 
march 2019 by paulbradshaw
In the Future, Video Games Will Care About You – Member Feature Stories – Medium
Eight years ago, game developer Bethesda attempted a radical experiment with its epic role-playing adventure Skyrim — and it went horribly, beautifully wrong. To make players feel like they were a… via Pocket
pocket  games  personalisation 
february 2019 by jburkunk

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