SentiWS - A Publicly Available German-language Resource for Sentiment Analysis

By Robert Remus, Uwe Quasthoff, Gerhard Heyer. International Conference on Language Resources and Evaluation, 2010

308 citations recorded by the source corpus.

SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, opinion mining etc. It lists positive and negative sentiment bearing words weighted within the interval of [-1; 1] plus their part of speech tag, and if applicable, their inflections. The current version of SentiWS (v1.8b) contains 1,650 negative and 1,818 positive words, which sum up to 16,406 positive and 16,328 negative word forms, respectively. It not only contains adjectives and adverbs explicitly expressing a sentiment, but also nouns and verbs implicitly containing one. The present work describes the resource’s structure, the three sources utilised to assemble it and the semi-supervised method incorporated to weight the strength of its entries. Furthermore the resource’s contents are extensively evaluated using a German-language evaluation set we constructed. The evaluation set is verified being reliable and its shown that SentiWS provides a beneficial lexical resource for German-language sentiment analysis related tasks to build on.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/0a4abc352680d760cb3be2b9400c8ae4fd07a93d

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In Artificial Intelligence

1. J. M. Serrano
2. Orestis Papakyriakopoulos
3. F. Marco
4. Simon Hegelich

Citations in the corpus

• Bias in word embeddings (2020, methodology): “We also use the sentiment list developed by Remus et al.[80] that contains words of positive and negative polarity for a sentiment bias task.”
• Overview of the GermEval 2018 Shared Task on the Identification of Offensive Language (2018, unknown): “While 8 teams used no task-specific lexicon, 8 other teams used one or more publicly available lexicons, and 7 teams created a new lexicon.10 9 teams used polarity lexicons, chief among them PolArt (Klenner et al., 2009), PolarityClues (Waltinger, 2010) and SentiWS (Remus et al., 2010), and 8 teams ”