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.2021.37
URN: urn:nbn:de:0030-drops-145734
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/14573/
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Kern, Bettina M. J. ; Baumann, Andreas ; Kolb, Thomas E. ; Sekanina, Katharina ; Hofmann, Klaus ; Wissik, Tanja ; Neidhardt, Julia

A Review and Cluster Analysis of German Polarity Resources for Sentiment Analysis

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OASIcs-LDK-2021-37.pdf (0.6 MB)

Abstract

The domain of German polarity dictionaries is heterogeneous with many small dictionaries created for different purposes and using different methods. This paper aims to map out the landscape of freely available German polarity dictionaries by clustering them to uncover similarities and shared features. We find that, although most dictionaries seem to agree in their assessment of a word’s sentiment, subsets of them form groups of interrelated dictionaries. These dependencies are in most cases an immediate reflex of how these dictionaries were designed and compiled. As a consequence, we argue that sentiment evaluation should be based on multiple and diverse sentiment resources in order to avoid error propagation and amplification of potential biases.

BibTeX - Entry

@InProceedings{kern_et_al:OASIcs.LDK.2021.37,
  author =	{Kern, Bettina M. J. and Baumann, Andreas and Kolb, Thomas E. and Sekanina, Katharina and Hofmann, Klaus and Wissik, Tanja and Neidhardt, Julia},
  title =	{{A Review and Cluster Analysis of German Polarity Resources for Sentiment Analysis}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{37:1--37:17},
  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 =		{https://drops.dagstuhl.de/opus/volltexte/2021/14573},
  URN =		{urn:nbn:de:0030-drops-145734},
  doi =		{10.4230/OASIcs.LDK.2021.37},
  annote =	{Keywords: cluster analysis, sentiment polarity, sentiment analysis, German, review}
}

Keywords: cluster analysis, sentiment polarity, sentiment analysis, German, review
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021
Supplementary Material: Software (Source Code): https://github.com/bettina-mj-kern/LDK_2021

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