Triangulating Temporal Dynamics in Multilingual Swiss Online News

• URL: http://arxiv.org/abs/2603.21519v1
• Date: Mon, 23 Mar 2026 03:27:00 GMT
• Title: Triangulating Temporal Dynamics in Multilingual Swiss Online News
• Abstract summary: This paper studies temporal trends in Swiss digital media across the country's three main linguistic regions, French, German, and Italian.<n>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.<n>The findings reveal distinct temporal patterns and highlight how linguistic and cultural contexts influence reporting.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

Related papers

• BOUTEF: A Multilingual Corpus for FakeNews in North Africa -- Language as a Weapon [0.7437224586066944]
  BOUTEF is a large-scale multilingual corpus designed to study the propagation, characteristics, and impact of fake news in Algeria and Tunisia.<n>It covers a wide range of languages and linguistic varieties, including MSA, Algerian and Tunisian dialects, Arabizi, French, English, and code-switched language.
  arXiv  Detail & Related papers  (2026-05-29T16:27:47Z)
• When Meanings Meet: Investigating the Emergence and Quality of Shared Concept Spaces during Multilingual Language Model Training [57.230355403478995]
  We investigate the development of language-agnostic concept spaces during pretraining of EuroLLM.<n>We find that shared concept spaces emerge early and continue to refine, but that alignment with them is language-dependent.<n>In contrast to prior work, our fine-grained manual analysis reveals that some apparent gains in translation quality reflect shifts in behavior.
  arXiv  Detail & Related papers  (2026-01-30T11:23:01Z)
• Multilingual Vision-Language Models, A Survey [0.9722250595763385]
  This survey examines multilingual vision-language models that process text and images across languages.<n>We review 31 models and 21 benchmarks, spanning encoder-only and generative architectures.
  arXiv  Detail & Related papers  (2025-09-26T09:46:13Z)
• Social Bias in Multilingual Language Models: A Survey [5.756606441319472]
  This systematic review analyzes emerging research that extends bias evaluation and mitigation approaches into multilingual and non-English contexts.<n>We examine these studies with respect to linguistic diversity, cultural awareness, and their choice of evaluation metrics and mitigation techniques.
  arXiv  Detail & Related papers  (2025-08-27T18:25:32Z)
• Towards Explainable Bilingual Multimodal Misinformation Detection and Localization [64.37162720126194]
  BiMi is a framework that jointly performs region-level localization, cross-modal and cross-lingual consistency detection, and natural language explanation for misinformation analysis.<n>BiMiBench is a benchmark constructed by systematically editing real news images and subtitles.<n>BiMi outperforms strong baselines by up to +8.9 in classification accuracy, +15.9 in localization accuracy, and +2.5 in explanation BERTScore.
  arXiv  Detail & Related papers  (2025-06-28T15:43:06Z)
• Re-calibrating methodologies in social media research: Challenge the visual, work with Speech [0.0]
  This article reflects on how social media scholars can effectively engage with speech-based data in their analyses.<n>I conclude that the expansion of our methodological repertoire enables richer interpretations of platformised content.
  arXiv  Detail & Related papers  (2024-12-17T18:47:57Z)
• Multilingual Topic Classification in X: Dataset and Analysis [19.725017254962918]
  We introduce X-Topic, a multilingual dataset featuring content in four distinct languages (English, Spanish, Japanese, and Greek) Our dataset includes a wide range of topics, tailored for social media content, making it a valuable resource for scientists and professionals working on cross-linguistic analysis.
  arXiv  Detail & Related papers  (2024-10-04T01:37:26Z)
• Combining Objective and Subjective Perspectives for Political News Understanding [5.741243797283764]
  We introduce a text analysis framework which integrates both perspectives and provides a fine-grained processing of subjective aspects. We illustrate its functioning with insights on news outlets, political orientations, topics, individual entities, and demographic segments.
  arXiv  Detail & Related papers  (2024-08-20T20:13:19Z)
• Understanding Cross-Lingual Alignment -- A Survey [52.572071017877704]
  Cross-lingual alignment is the meaningful similarity of representations across languages in multilingual language models. We survey the literature of techniques to improve cross-lingual alignment, providing a taxonomy of methods and summarising insights from throughout the field.
  arXiv  Detail & Related papers  (2024-04-09T11:39:53Z)
• Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking [48.21982147529661]
  This paper introduces a novel approach for massively multicultural knowledge acquisition. Our method strategically navigates from densely informative Wikipedia documents on cultural topics to an extensive network of linked pages. Our work marks an important step towards deeper understanding and bridging the gaps of cultural disparities in AI.
  arXiv  Detail & Related papers  (2024-02-14T18:16:54Z)
• Multi-EuP: The Multilingual European Parliament Dataset for Analysis of Bias in Information Retrieval [62.82448161570428]
  This dataset is designed to investigate fairness in a multilingual information retrieval context. It boasts an authentic multilingual corpus, featuring topics translated into all 24 languages. It offers rich demographic information associated with its documents, facilitating the study of demographic bias.
  arXiv  Detail & Related papers  (2023-11-03T12:29:11Z)
• Bridging Linguistic Typology and Multilingual Machine Translation with Multi-View Language Representations [83.27475281544868]
  We use singular vector canonical correlation analysis to study what kind of information is induced from each source. We observe that our representations embed typology and strengthen correlations with language relationships. We then take advantage of our multi-view language vector space for multilingual machine translation, where we achieve competitive overall translation accuracy.
  arXiv  Detail & Related papers  (2020-04-30T16:25:39Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.