Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-1530
Publication type: | Conference paper |
Type of review: | Peer review (abstract) |
Title: | A Twitter corpus and benchmark resources for german sentiment analysis |
Authors: | Cieliebak, Mark Deriu, Jan Milan Egger, Dominic Uzdilli, Fatih |
DOI: | 10.21256/zhaw-1530 10.18653/v1/W17-1106 |
Page(s): | 45 |
Pages to: | 51 |
Conference details: | 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017 |
Issue Date: | 2017 |
Publisher / Ed. Institution: | Association for Computational Linguistics |
Language: | English |
Subjects: | Sentiment Analysis; Corpus; Twitter |
Subject (DDC): | 006: Special computer methods 410.285: Computational linguistics |
Abstract: | In this paper we present SB10k, a new corpus for sentiment analysis with approx.10,000 German tweets. We use this new corpus and two existing corpora to provide state-of-the-art bench-marks for sentiment analysis in German:we implemented a CNN (based on the winning system of SemEval-2016) and a feature-based SVM and compare their performance on all three corpora. For the CNN, we also created German word embeddings trained on 300M tweets. These word embeddings were then optimized for sentiment analysis using distant-supervised learning. The new corpus, the German word embeddings (plain and optimized), and source code to re-run the benchmarks are publicly available. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/1856 |
Fulltext version: | Published version |
License (according to publishing contract): | Licence according to publishing contract |
Departement: | School of Engineering |
Organisational Unit: | Institute of Applied Information Technology (InIT) |
Appears in collections: | Publikationen School of Engineering |
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Cieliebak, M., Deriu, J. M., Egger, D., & Uzdilli, F. (2017). A Twitter corpus and benchmark resources for german sentiment analysis [Conference paper]. 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017, 45–51. https://doi.org/10.21256/zhaw-1530
Cieliebak, M. et al. (2017) ‘A Twitter corpus and benchmark resources for german sentiment analysis’, in 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017. Association for Computational Linguistics, pp. 45–51. Available at: https://doi.org/10.21256/zhaw-1530.
M. Cieliebak, J. M. Deriu, D. Egger, and F. Uzdilli, “A Twitter corpus and benchmark resources for german sentiment analysis,” in 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017, 2017, pp. 45–51. doi: 10.21256/zhaw-1530.
CIELIEBAK, Mark, Jan Milan DERIU, Dominic EGGER und Fatih UZDILLI, 2017. A Twitter corpus and benchmark resources for german sentiment analysis. In: 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017. Conference paper. Association for Computational Linguistics. 2017. S. 45–51
Cieliebak, Mark, Jan Milan Deriu, Dominic Egger, and Fatih Uzdilli. 2017. “A Twitter Corpus and Benchmark Resources for German Sentiment Analysis.” Conference paper. In 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017, 45–51. Association for Computational Linguistics. https://doi.org/10.21256/zhaw-1530.
Cieliebak, Mark, et al. “A Twitter Corpus and Benchmark Resources for German Sentiment Analysis.” 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017, Association for Computational Linguistics, 2017, pp. 45–51, https://doi.org/10.21256/zhaw-1530.
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