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The seventh Digital News Report from the Reuters Institute for the Study of Journalism at the University of Oxford contains a wealth of data about consumption by brand, device and platform across countries. It focuses on the issues of trust, misinformation, changing business models and the role of platforms.

What strategies do public service media have for news distribution on social media? How do they organise their work? How do they react to changes in the ranking algorithms and products? A new Reuters Institute report looks at how public service news organisations in six European countries (Finland, France, Germany, Italy, Poland and the UK) deliver news via social media at a time when news use is increasingly driven by referrals or consumed off-site on various platforms. The analysis is based on 14 interviews conducted between November 2017 and January 2018, primarily with senior editors and managers for news, or social media for news specifically. We complement the interviews with various analyses of how public service media perform on social media. The social media platforms of our focus are Facebook, Twitter, and Instagram.

More and more news organisations are implementing paywalls, as legacy revenues continue to erode and digital advertising increasingly go to large technology companies. In this factsheet, we present an overview of the diffusion of different forms of pay models across a sample of 171 of the most important news organisations in six European countries (Finland, France, Germany, Italy, Poland, and the UK). Results show that different types of news organisations adopt diverse approaches. A clear majority of newspapers and weeklies operate a pay model (freemium, metered paywalls, hard paywalls), whereas all broadcasters and almost all digital-born sites offer free access to their news. Pay models adoption is widespread especially in Finland, France, and Poland, where from 87% to 95% of newspapers and weeklies have adopted paywalls. By contrast, in Italy, Germany and the UK, many of the most important news outlets continue to offer free access to their digital content.

In this RISJ Factsheet, we study Indian news audience distribution across Facebook and Twitter and compare it to that of the open web. To this end, we analyse data from the recently concluded Indian General Election which took place over multiple phases between 11 April and 19 May 2019, and broke the record for being the largest democratic exercise in the world. More than five thousand candidates ran for the 543 available seats in the Lok Sabha, the lower house of the Indian parliament, and nine hundred million eligible voters were called to the polls, of which over 67% turned up to vote. We find that while vernacular or regional newspapers dominated the provision of news on Facebook, digital-born as well as legacy national level outlets were more active in posting news updates on Twitter. Audiences on Facebook as well as Twitter however were more engaged with digital-born outlets, both national as well as regional. Finally, we find no evidence of fragmentation in how the online Indian audience consumed news during the election period.

The eighth Digital News Report from the Reuters Institute for the Study of Journalism at the University of Oxford reveals that public concern about misinformation is making some people more careful about the brands they choose and the content they share online. The report, which is based on a YouGov survey conducted with 75,000 people in 38 markets, says that changing behaviour is most apparent with those that are younger and better educated, rather than older or less privileged groups. Across countries over a quarter (26%) say they are relying on more ‘reputable’ sources of news than this time last year – rising to 40% in the US. A further quarter (24%) said they had stopped using sources with a dubious reputation. The report also brings new comparative data on changing online business models, trust, misinformation, the rise of messaging apps and the impact of populism on media usage.

This report is a snapshot of the development of news consumption habits in India and how the rise of mobile media, social media platforms, and messaging applications is in the process of changing how Indians access news and engage with it. It is a pilot study that deals exclusively with English-language news users with internet access, a small, but important, subset of a larger, more diverse, and very complex Indian media market. Our findings show that this subset of users are embracing a mobile-first, platform-dominated media environment with search engines, social media, and messaging applications playing an absolutely key role in how people access and use news in an setting characterised by low trust in many news media, high concerns over the possible implications of expressing political views, and widespread worries about different kinds of disinformation.

In recent decades, processes including particles like fermentation, flocculation, precipitation and crystallization have become essential parts of various bioprocesses. In many of these processes, particle properties are direct or indirect measures of product quality and process efficiency (Redman & O’Grady, 2017). With the currently increasing demand for optimizing these processes and ensuring more consistent product properties, there has been a renewed focus on continuous particle analysis, which previously has been too time consuming task. Recent advances in advanced image analysis have now opened up for directly measuring and analysing particles in real time. In this work, a generic real-time monitoring and modelling framework for particle processes is presented, based on population balance modelling, utilizing deep-learning techniques for rate-estimations. Using a novel flow-cell microscopy setup, captured microscopy images are continuously provided as inputs to the neural network alongside the controlled process variables including temperature and pH at the current and a given future time. The neural network will here estimate the rates for particle birth, growth and death, and provide forecasts of the particle size/shape distributions at the future time, by solving a generic population balance model. The training of the neural network model can be carried out in real-time, whilst the given process is running, continuously improving the process model, and hence the generated process forecast. The framework is demonstrated through an industrial scale pharmaceutical crystallization case study. Here it is shown that by using the raw images as an input to the neural network, it is possible to effectively pick up visually detectable disturbances, which can then be taken into account in the model predictions, improving the model predictions significantly in comparison to only using the controlled process variables as inputs.

We examine the editorial and business strategies of 13 European digital-born news media organisations. Although the last two years have been difficult for ad-supported models, advertising remains vital for most. We see an increasing interest in subscription and membership models as long-term (but not difficulty-free) revenue sources. Digital-born news media are subject to similar pressures to their legacy counterparts. The sector is not characterised by winner-take-all economics, but on establishing lean, sustainable funding models using diverse revenue sources. Organisations continue to balance the risks and opportunities of working with platforms like Facebook and Google. Recent changes to the Facebook algorithm hurt some, but media continue to engage for reach and audience engagement. We find evidence of a flight to quality, with the difficult funding landscape and desire to build paying audiences driving an emphasis on quality rather than clicks. We also find increased interest in connecting with non-traditional audiences.

Search engines are an absolutely central part of the web. Yet we know relatively little about how they shape news consumption. In this study, we use survey data from four countries (UK, USA, Germany, Spain) to compare the news repertoires of those who say they use search engines to search for news stories, and those that do not. In all four countries, and controlling for other factors, we show that those who find news via search engines (i) on average use more sources of online news, (ii) are more likely to use both left-leaning and right-leaning online news sources, and (iii) have more balanced news repertoires in terms of using similar numbers of left-leaning and right-leaning sources. We thus find little support for the idea that search engine use leads to echo chambers and filter bubbles. To the contrary, using search engines for news is associated with more diverse and more balanced news consumption, as search drives what we call “automated serendipity” and leads people to sources they would not have used otherwise.

In this report, we examine how private sector legacy news organisations across six European countries use social media for news distribution. We analyse in particular how strategies vary across different news organisations and across platforms, with a section focusing on how publishers have responded to the January 2018 changes to Facebook’s algorithm. Based on 21 interviews with editors and mangers at 12 newspapers and commercial broadcasters, we find that, even though many news organisations are frustrated by limited direct monetisation and frequent algorithm changes, they still concentrate on Facebook their resources for social media distribution. The impact of Facebook algorithm change varies across organisations, but is in most cases far from the apocalyptic scenarios anticipated by some commentators. There is no clear pattern to explain this variation, but broadly the organisations that increased their activity on Facebook have seen a smaller decline in interactions than others, and in some cases growth.

Most of the content, products, and services we use online, whether provided by media organisations or by technology companies, are funded in whole or in part by advertising and various forms of marketing. Such advertising, and more broadly many other online services, increasingly involves the collection and analysis of large amounts of personal information that we wittingly or unwittingly let websites collect as we use them, personal information that is in turn often shared with various third parties through third- party elements and cookies included when we load a website, oftentimes without users’ consent or even disclosure. This factsheet provides an overview of third-party web content practices involved in such data collection. We focus on a sample of major news sites in seven EU countries, compare news sites with popular sites, and explore differences between the countries covered. Analysis of millions of content requests and cookies helps us measure the amount of third-party elements and cookies included on news sites and other popular sites, identify the companies involved, and categorise the different types of third-party content found. Across all countries, we find that news sites include significantly higher volumes of third-party content and cookies compared with other popular sites. On average, news sites load four times as many third- party domains (40 vs 10) and set almost eight times as many third-party cookies (81 vs 12).