My Friends, Editors, Algorithms, and I

Abstract

Prompted by the ongoing development of content personalization by social networks and mainstream news brands, and recent debates about balancing algorithmic and editorial selection, this study explores what audiences think about news selection mechanisms and why. Analysing data from a 26-country survey (N ¼ 53,314), we report the extent to which audiences believe story selection by editors and story selection by algorithms are good ways to get news online and, using multi-level models, explore the relationships that exist between individuals' characteristics and those beliefs. The results show that, collectively, audiences believe algorithmic selection guided by a user's past consumption behaviour is a better way to get news than editorial curation. There are, however, significant variations in these beliefs at the individual level. Age, trust in news, concerns about privacy, mobile news access, paying for news, and six other variables had effects. Our results are partly in line with current general theory on algorithmic appreciation, but diverge in our findings on the relative appreciation of algorithms and experts, and in how the appreciation of algorithms can differ according to the data that drive them. We believe this divergence is partly due to our study's focus on news, showing algorithmic appreciation has context-specific characteristics.

On the Democratic Role of News Recommenders

“…Many citizens consider recommenders a good way to get the news and to navigate their way through the growing abundance of information, and in some circumstances they even consider them preferable to journalistically curated choices (Thurman et al 2018). The ability to filter and customise the information offer enables the media to be more responsive to the concrete information needs of users, and brings journalists one step closer to truly engaging with their audience.…”

Algorithmic social media use and its relationship to attitude reinforcement and issue-specific political participation – The case of the 2015 European immigration movements

“…However, citizens who become more extreme in their attitude toward immigration over time are found to be less likely to become politically active regarding this specific issue. The algorithmic filtering of media content is a core concern for a digital society (Thurman, Moeller, Helberger, & Trilling, 2019). Media are important sources of information in the formation of political viewpoints and affect citizens' democratic participation (Delli Carpini, Cook, & Jacobs, 2004;Downs, 1957).…”

Social media and its intersections with free speech, freedom of information and privacy. An analysis

“…Those algorithms are key parts of the technological development of social media and other Internet based platforms and environment, even though only 29% of people know that Algorithms are responsible of the information which appears at their timelines and social media news feeds (Digital News report, 2018). Even though, algorithmic selection is starting to be more appreciated by users than traditional editorial curation as a response to the perception of excessive media bias, among other factors (Thurman, Moeller, Helberger, & Trilling, 2018).…”