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https://doi.org/10.21256/zhaw-1530| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Abstract) |
| Titel: | A Twitter corpus and benchmark resources for german sentiment analysis |
| Autor/-in: | Cieliebak, Mark Deriu, Jan Milan Egger, Dominic Uzdilli, Fatih |
| DOI: | 10.21256/zhaw-1530 10.18653/v1/W17-1106 |
| Seite(n): | 45 |
| Seiten bis: | 51 |
| Angaben zur Konferenz: | 5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017 |
| Erscheinungsdatum: | 2017 |
| Verlag / Hrsg. Institution: | Association for Computational Linguistics |
| Sprache: | Englisch |
| Schlagwörter: | Sentiment Analysis; Corpus; Twitter |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren 410.285: Computerlinguistik |
| Zusammenfassung: | 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 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 10_Paper.pdf | 516.72 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
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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