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Conference object . 2026
License: CC BY
Data sources: Datacite
ZENODO
Conference object . 2026
License: CC BY
Data sources: Datacite
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MORCDA - Making Open Research Data Suitable for Comparative Discourse Analysis - Project Poster 2nd OSCARS AGM 2026

Authors: Dreesen, Philipp; Czachur, Waldemar; Evert, Stephanie; Rocco, Goranka; Grisot, Cristina;

MORCDA - Making Open Research Data Suitable for Comparative Discourse Analysis - Project Poster 2nd OSCARS AGM 2026

Abstract

The promotion of a European public sphere is critical for the cultivation of democratic discourse and opinion formation. In this context, discourse analysis offers profound insights into transnational media discourses, supported by multilingual and comparative perspectives. Recent advancements in discourse analysis leverage machine learning and corpus analysis, expanding the scope for cross-border linguistic research. However, the full potential of Open Research Data (ORD) for comparative, multilingual discourse analysis remains underutilised. The MORCDA project seeks to bridge gaps between comparative discourse researchers and open research data communities, facilitating the adoption of ORD practices and optimising research infrastructures (RIs) for enhanced comparative analysis across European languages and contexts.

Keywords

Discourse Analysis, Corpus Linguistics, ORD, Language, Comparative Studies, FAIR

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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