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GerVADER Sentiment-Analysis-Tool

Based on VADER GerVADER allows for german sentiment-analysis without requiring Machine Learning or translation services. Its rule-based algorithm allows for a quick sentiment rating of the users texts.
GerVADER on GitHub
Work in progress. Come back later.

publications

Detecting soiling on solar panels with datamining and machine learning

Published in Adjunct Proceedings of the 33rd edition of the EnviroInfo – the long standing and established international and interdisciplinary conference series on leading environmental information and communication technologies, 2019

The paper deals with detecting soiled solar panels just by means of collected data of a solar plant.

Work in progress. Come back later.

Recommended citation: Das Buch Rüdiger Schaldach, Karl-Heinz Simon, Jens Weismüller, Volker Wohlgemuth (eds.) - Environmental Informatics: Computational Sustainability: ICT methods to achieve the UN Sustainable Development Goals Adjunct Proceedings of the 33rd edition of the EnviroInfo – the long standing and established international and interdisciplinary conference series on leading environmental information and communication technologies (ISBN: 978-3-8440-6847-4) wurde im Shaker Verlag veröffentlicht. http://www.shaker.de/shop/978-3-8440-6847-4

GerVADER - A German Adaptation of the VADER Sentiment Analysis Tool for Social Media Texts

Published in Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen - LWDA2019, 2019

GerVADER is a German adaptation of the sentiment classification tool VADER. VADER is a lexicon and rule-based approach in classifying sentences into positive, negative or neutral statements and puts a focus on social media texts.

Work in progress. Come back later.

Recommended citation: Karsten Michael Tymann, Matthias Lutz, Patrick Palsbröker and Carsten Gips: GerVADER - A German adaptation of the VADER sentiment analysis tool for social media texts. In Proceedings of the Conference "Lernen, Wissen, Daten, Analysen" (LWDA 2019), Berlin, Germany, September 30 - October 2, 2019. http://ceur-ws.org/Vol-2454/paper_14.pdf

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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