@inproceedings{brun-nikoulina-2018-aspect,
title = "Aspect Based Sentiment Analysis into the Wild",
author = "Brun, Caroline and
Nikoulina, Vassilina",
editor = "Balahur, Alexandra and
Mohammad, Saif M. and
Hoste, Veronique and
Klinger, Roman",
booktitle = "Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis",
month = oct,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6217",
doi = "10.18653/v1/W18-6217",
pages = "116--122",
abstract = "In this paper, we test state-of-the-art Aspect Based Sentiment Analysis (ABSA) systems trained on a widely used dataset on actual data. We created a new manually annotated dataset of user generated data from the same domain as the training dataset, but from other sources and analyse the differences between the new and the standard ABSA dataset. We then analyse the results in performance of different versions of the same system on both datasets. We also propose light adaptation methods to increase system robustness.",
}
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%0 Conference Proceedings
%T Aspect Based Sentiment Analysis into the Wild
%A Brun, Caroline
%A Nikoulina, Vassilina
%Y Balahur, Alexandra
%Y Mohammad, Saif M.
%Y Hoste, Veronique
%Y Klinger, Roman
%S Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F brun-nikoulina-2018-aspect
%X In this paper, we test state-of-the-art Aspect Based Sentiment Analysis (ABSA) systems trained on a widely used dataset on actual data. We created a new manually annotated dataset of user generated data from the same domain as the training dataset, but from other sources and analyse the differences between the new and the standard ABSA dataset. We then analyse the results in performance of different versions of the same system on both datasets. We also propose light adaptation methods to increase system robustness.
%R 10.18653/v1/W18-6217
%U https://aclanthology.org/W18-6217
%U https://doi.org/10.18653/v1/W18-6217
%P 116-122
Markdown (Informal)
[Aspect Based Sentiment Analysis into the Wild](https://aclanthology.org/W18-6217) (Brun & Nikoulina, WASSA 2018)
ACL
- Caroline Brun and Vassilina Nikoulina. 2018. Aspect Based Sentiment Analysis into the Wild. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 116–122, Brussels, Belgium. Association for Computational Linguistics.