License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.26
URN: urn:nbn:de:0030-drops-145623
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Krasselt, Julia ; Fluor, Matthias ; Rothenhäusler, Klaus ; Dreesen, Philipp

A Workbench for Corpus Linguistic Discourse Analysis

OASIcs-LDK-2021-26.pdf (0.8 MB)


In this paper, we introduce the Swiss-AL workbench, an online tool for corpus linguistic discourse analysis. The workbench enables the analysis of Swiss-AL, a multilingual Swiss web corpus with sources from media, politics, industry, science, and civil society. The workbench differs from other corpus analysis tools in three characteristics: (1) easy access and tidy interface, (2) focus on visualizations, and (3) wide range of analysis options, ranging from classic corpus linguistic analysis (e.g., collocation analysis) to more recent NLP approaches (topic modeling and word embeddings). It is designed for researchers of various disciplines, practitioners, and students.

BibTeX - Entry

  author =	{Krasselt, Julia and Fluor, Matthias and Rothenh\"{a}usler, Klaus and Dreesen, Philipp},
  title =	{{A Workbench for Corpus Linguistic Discourse Analysis}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{26:1--26:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-145623},
  doi =		{10.4230/OASIcs.LDK.2021.26},
  annote =	{Keywords: corpus analysis software, discourse analysis, data visualization}

Keywords: corpus analysis software, discourse analysis, data visualization
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021
Supplementary Material: InteractiveResource (Online Tool):

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