Where did you come from, where did you go? News trajectories in Germany and Switzerland

Mykola Makhortykh, Ernesto León, Aleksandra Urman () and Teresa Gil-López
Additional contact information
Mykola Makhortykh: University of Bern
Ernesto León: University of Amsterdam
Aleksandra Urman: University of Zürich
Teresa Gil-López: Universidad Carlos III de Madrid

Journal of Computational Social Science, 2025, vol. 8, issue 2, No 7, 21 pages

Abstract: Abstract The article examines news trajectories used by individuals to access mainstream journalistic media in Germany and German-speaking Switzerland during the first peak of COVID-19 in Europe. It discusses the role of individual characteristics related to sociodemographics, political, and media attitudes in predisposition towards specific modes of news access. For this aim, it combines survey data with data on individuals’ engagement with news automatically tracked in spring 2020. The findings of the article highlight the prevalence of accessing news via search engines (search trajectory) and by directly going to news websites (routine trajectory). The study also demonstrates the important role of political and media attitudes in the prevalence of specific modes of news access, which, however, differs between the countries, thus emphasizing the importance of conducting more comparative research using tracking data.

Keywords: News; News consumption; Web tracking; Comparative (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42001-025-00361-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:8:y:2025:i:2:d:10.1007_s42001-025-00361-3

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-025-00361-3

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().