@inproceedings{hoang-etal-2019-aspect,
title = "Aspect-Based Sentiment Analysis using {BERT}",
author = "Hoang, Mickel and
Bihorac, Oskar Alija and
Rouces, Jacobo",
editor = "Hartmann, Mareike and
Plank, Barbara",
booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
month = sep # "{--}" # oct,
year = "2019",
address = "Turku, Finland",
publisher = {Link{\"o}ping University Electronic Press},
url = "https://aclanthology.org/W19-6120",
pages = "187--196",
abstract = "Sentiment analysis has become very popular in both research and business due to the increasing amount of opinionated text from Internet users. Standard sentiment analysis deals with classifying the overall sentiment of a text, but this doesn{'}t include other important information such as towards which entity, topic or aspect within the text the sentiment is directed. Aspect-based sentiment analysis (ABSA) is a more complex task that consists in identifying both sentiments and aspects. This paper shows the potential of using the contextual word representations from the pre-trained language model BERT, together with a fine-tuning method with additional generated text, in order to solve out-of-domain ABSA and outperform previous state-of-the-art results on SemEval-2015 Task 12 subtask 2 and SemEval-2016 Task 5. To the best of our knowledge, no other existing work has been done on out-of-domain ABSA for aspect classification.",
}
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%0 Conference Proceedings
%T Aspect-Based Sentiment Analysis using BERT
%A Hoang, Mickel
%A Bihorac, Oskar Alija
%A Rouces, Jacobo
%Y Hartmann, Mareike
%Y Plank, Barbara
%S Proceedings of the 22nd Nordic Conference on Computational Linguistics
%D 2019
%8 sep–oct
%I Linköping University Electronic Press
%C Turku, Finland
%F hoang-etal-2019-aspect
%X Sentiment analysis has become very popular in both research and business due to the increasing amount of opinionated text from Internet users. Standard sentiment analysis deals with classifying the overall sentiment of a text, but this doesn’t include other important information such as towards which entity, topic or aspect within the text the sentiment is directed. Aspect-based sentiment analysis (ABSA) is a more complex task that consists in identifying both sentiments and aspects. This paper shows the potential of using the contextual word representations from the pre-trained language model BERT, together with a fine-tuning method with additional generated text, in order to solve out-of-domain ABSA and outperform previous state-of-the-art results on SemEval-2015 Task 12 subtask 2 and SemEval-2016 Task 5. To the best of our knowledge, no other existing work has been done on out-of-domain ABSA for aspect classification.
%U https://aclanthology.org/W19-6120
%P 187-196
Markdown (Informal)
[Aspect-Based Sentiment Analysis using BERT](https://aclanthology.org/W19-6120) (Hoang et al., NoDaLiDa 2019)
ACL
- Mickel Hoang, Oskar Alija Bihorac, and Jacobo Rouces. 2019. Aspect-Based Sentiment Analysis using BERT. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 187–196, Turku, Finland. Linköping University Electronic Press.