The Future of Personalisation at News Websites: Lessons from a Longitudinal Study

This paper tracks the recent history of personalization at national news websites in the United Kingdom and United States, allowing an analysis to be made of the reasons for and implications of the adoption of this form of adaptive interactivity. Using three content surveys conducted over three and a half years, the study records—at an unprecedented level of detail—the range of personalization features offered by contemporary news websites, and demonstrates how news organizations increasingly rely on software algorithms to predict readers’ content preferences. The results also detail how news organizations’ deployment of personalization on mobile devices, and in conjunction with social networking platforms, is still at an early stage. In addressing the under-researched but important—and increasingly prevalent—phenomenon of personalization, this paper contributes to debates on journalism’s future funding, transparency, and societal benefits

Financial capability, the financial crisis, and trust in news media

Since the Global Financial Crisis of 2008 the financial media has been analysed from the perspectives of experts and far less from the audiences who consume it. This article fills this gap by exploring public consumption of financial news and their levels of satisfaction. It explores another, less researched, issue; that of financial literacy, which is a major impediment to public understanding and is weaker among women, young people and the less affluent. Consequently, the study makes the following suggestions: financial journalism needs to respond to a wide audience and provide more useful, unbiased and accessible financial news; personal finance news, which is an under-researched genre, could build financial capability levels and might improve trust between media and its audiences; and the financial media should be considered a key player by policy-makers if they want to bolster financial capabilit

Giving Computers a Nose for News: Exploring the limits of story detection and verification

The use of social media as a source of news is entering a new phase as computer algorithms are developed and deployed to detect, rank, and verify news. The efficacy and ethics of such technology is the subject of this article, which examines the SocialSensor application, a tool developed by a multidisciplinary European Union research project. The results suggest that computer software can be used successfully to identify trending news stories, allow journalists to search within a social media corpus, and help verify social media contributors and content. However, such software also raises questions about accountability as social media is algorithmically filtered for use by journalists and others. Our analysis of the inputs SocialSensor relies on shows biases towards those who are vocal and have an audience, many of whom are men in the media. We also reveal some of the technology’s temporal and topic preferences. The conclusion discusses whether such biases are necessary for systems like SocialSensor to be effective. The article also suggests that academic research has failed to recognise fully the changes to journalists’ sourcing practices brought about by social media, particularly Twitter, and provides some countervailing evidence and an explanation for this failure

Building the ‘Truthmeter’: Training algorithms to help journalists assess the credibility of social media sources

Social media is now used as an information source in many different contexts. For professional journalists, the use of social media for news production creates new challenges for the verification process. This article describes the development and evaluation of the ‘Truthmeter’ – a tool that automatically scores the journalistic credibility of social media contributors in order to inform overall credibility assessments. The Truthmeter was evaluated using a threestage process that used both qualitative and quantitative methods, consisting of (1) obtaining a ground truth, (2) building a description of existing practices, and (3) calibration, modification and testing. As a result of the evaluation process, which could be generalized and applied in other contexts, the Truthmeter produced credibility scores that were closely aligned with those of trainee journalists. Substantively, the evaluation also highlighted the importance of ‘relational’ credibility assessments, where credibility may be attributed based on networked connections to other credible contributors

Identifying and verifying news through social media: Developing a user-centred tool for professional journalists

Identifying and verifying new information quickly are key issues for journalists who use social media. This article examines what tools journalists think they need to cope with the growing volume and complexity of news on social media, and what improvements are needed in existing systems. It gives some initial results from a major EU research project (Social Sensor), involving computer scientists, journalists, and media researchers, that is designing a new tool to search across social media for news stories, to surface trends, and to help with verification. Preliminary results suggest that an effective tool should focus on the role of key influencers, and should be customisable to suit the particular needs of individual journalists and news organisations