From text to insight: Uncovering linguistic patterns with SWEGRAM

dc.contributor.authorMegyesi, Beáta
dc.contributor.authorRuan, Rex
dc.contributor.editorBouma, Gerlof
dc.contributor.editorDannélls, Dana
dc.contributor.editorKokkinakis, Dimitrios
dc.contributor.editorVolodina, Elena
dc.date.accessioned2025-11-10T12:12:53Z
dc.date.available2025-11-10T12:12:53Z
dc.date.issued2025-11
dc.description.abstractEmpirical linguistic analysis provides valuable insights into textual data for researchers in the humanities and social sciences, enabling them to identify patterns and trends within large datasets. SWEGRAM is a freely available tool designed to annotate and analyze Swedish and English texts without requiring programming skills or a user account. Users can upload one or more texts for linguistic analysis, extracting morphological and syntactic features. The linguistically annotated texts can then be used for quantitative linguistic analysis, allowing researchers to systematically explore textual characteristics. Additionally, the tool visualizes syntactic relations between words in sentences and provides detailed insights into the distribution of syntactic functions and relations within the text. Users can also create their own linguistically annotated text collections and generate statistical summaries of the linguistic properties of their texts. The tool is available as both a web-based service, which requires no user login or account, and a downloadable version for local use when data privacy and security are a priority. This dual availability ensures accessibility and flexibility for diverse research needs.
dc.identifier.isbn9789908536125
dc.identifier.urihttps://hdl.handle.net/10062/117349
dc.identifier.urihttps://doi.org/10.58009/aere-perennius0179
dc.language.isoen
dc.publisherUniversity of Tartu Library
dc.relation.ispartofHuminfra handbook: Empowering digital and experimental humanities
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleFrom text to insight: Uncovering linguistic patterns with SWEGRAM
dc.typeArticle

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