CLCYMar 23

Triangulating Temporal Dynamics in Multilingual Swiss Online News

arXiv:2603.215195.3
AI Analysis

This study addresses the limited comprehensive analysis of multilingual media ecosystems, offering insights for media studies in diverse societies, though it is incremental in applying existing methods to a new context.

The paper tackled the problem of analyzing temporal trends in multilingual Swiss digital media by collecting over 1.7 million news articles and applying a triangulated methodology, revealing distinct patterns influenced by linguistic and cultural contexts.

Analyzing news coverage in multilingual societies can offer valuable insights into the dynamics of public discourse and the development of collective narratives, yet comprehensive studies that account for linguistic and cultural diversity within national media ecosystems remain limited, particularly in complex contexts such as Switzerland. This paper studies temporal trends in Swiss digital media across the country's three main linguistic regions, French, German, and Italian, using a triangulated methodology that combines quantitative analyses with qualitative insights. We collected and processed over 1.7 million news articles, applying lexical metrics, named entity recognition and Wikidata-based linking, targeted sentiment analysis, and consensus-based change-point detection. To enable principled cross-language comparisons and to connect to theories of domestication and cultural proximity, we derive domestication profiles together with a proximity salience ratio. Our analysis spans thematic, recurrent, and singular events. By integrating quantitative data with qualitative interpretation, we provide new insights into the dynamics of Swiss digital media and demonstrate the usefulness of triangulation in media studies. The findings reveal distinct temporal patterns and highlight how linguistic and cultural contexts influence reporting. Our approach offers a framework applicable to other multilingual or culturally diverse media environments, contributing to a deeper understanding of how news is shaped by linguistic and cultural factors.

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