@inproceedings{staliunaite-bonfil-2017-breaking,
title = "Breaking Sentiment Analysis of Movie Reviews",
author = "Stali{\=u}nait{\.e}, Ieva and
Bonfil, Ben",
editor = "Bender, Emily and
Daum{\'e} III, Hal and
Ettinger, Allyson and
Rao, Sudha",
booktitle = "Proceedings of the First Workshop on Building Linguistically Generalizable {NLP} Systems",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-5410",
doi = "10.18653/v1/W17-5410",
pages = "61--64",
abstract = "The current paper covers several strategies we used to {`}break{'} predictions of sentiment analysis systems participating in the BLGNLP2017 workshop. Specifically, we identify difficulties of participating systems in understanding modals, subjective judgments, world-knowledge based references and certain differences in syntax and perspective.",
}
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%0 Conference Proceedings
%T Breaking Sentiment Analysis of Movie Reviews
%A Staliūnaitė, Ieva
%A Bonfil, Ben
%Y Bender, Emily
%Y Daumé III, Hal
%Y Ettinger, Allyson
%Y Rao, Sudha
%S Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F staliunaite-bonfil-2017-breaking
%X The current paper covers several strategies we used to ‘break’ predictions of sentiment analysis systems participating in the BLGNLP2017 workshop. Specifically, we identify difficulties of participating systems in understanding modals, subjective judgments, world-knowledge based references and certain differences in syntax and perspective.
%R 10.18653/v1/W17-5410
%U https://aclanthology.org/W17-5410
%U https://doi.org/10.18653/v1/W17-5410
%P 61-64
Markdown (Informal)
[Breaking Sentiment Analysis of Movie Reviews](https://aclanthology.org/W17-5410) (Staliūnaitė & Bonfil, 2017)
ACL
- Ieva Staliūnaitė and Ben Bonfil. 2017. Breaking Sentiment Analysis of Movie Reviews. In Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems, pages 61–64, Copenhagen, Denmark. Association for Computational Linguistics.