And the next speaker in this session at the ECREA 2026 conference in Brno is the great Cornelius Puschmann, whose focus is on mapping mobile news pathways. It’s clear that the media landscape has shifted, and is continuing to shift: this has produced both fragmentation and convergence in what news people access, and how they do so – e.g. through various social media platforms and apps. These platforms now also provide a vastly expanded content ecosystem, blending diverse conventional and emerging sources and formats.
This is shaped by device and platform affordances that affect visibility, personalisation, network association, editability, and searchability; in combination, these shape the news pathways that users navigate. Education, socioeconomic status, political interest, gender, and age also affect the extent which people actively seek out and consume news content.
How can we explore news exposure on mobile devices and platforms, then? This project pursues a mixed-methods approach: it works with a broadly representative sample of German news users on Android devices, and engages in mobile use tracking as well as administering a survey to these users. This draws on Muramura’s tracking application for in-app activity tracking, which utilises Android’s accessibility functionality, and in the end extracts video creator names and descriptions for YouTube, TikTok, and video news apps.
Only some one third of YouTube content is news content; for TikTok this rises to three quarters; while all news app content is news, of course. YouTube and news app news consumption are also a great deal more regular.
Political interest, social media use, and AI use are strong predictors, while male users also use news much more than female users. The impact of political interest is also much more pronounced for YouTube than the other sources. TV users use TikTok and YouTube a lot less; radios users use news apps a lot less.
News pathways thus vary considerably, as does the type of exposure, and this is also affected by intentional or algorithmic pathways. Age does not appear to be a relevant predictor, while platforms like TikTok also seem to expose non-news consumers to the news.
