@inproceedings{vorakitphan-etal-2020-regrexit,
title = "Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts",
author = "Vorakitphan, Vorakit and
Guerini, Marco and
Cabrio, Elena and
Villata, Serena",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.19",
doi = "10.18653/v1/2020.coling-main.19",
pages = "219--224",
abstract = "Emotion analysis in polarized contexts represents a challenge for Natural Language Processing modeling. As a step in the aforementioned direction, we present a methodology to extend the task of Aspect-based Sentiment Analysis (ABSA) toward the affect and emotion representation in polarized settings. In particular, we adopt the three-dimensional model of affect based on Valence, Arousal, and Dominance (VAD). We then present a Brexit scenario that proves how affect varies toward the same aspect when politically polarized stances are presented. Our approach captures aspect-based polarization from newspapers regarding the Brexit scenario of 1.2m entities at sentence-level. We demonstrate how basic constituents of emotions can be mapped to the VAD model, along with their interactions respecting the polarized context in ABSA settings using biased key-concepts (e.g., {``}stop Brexit{''} vs. {``}support Brexit{''}). Quite intriguingly, the framework achieves to produce coherent aspect evidences of Brexit{'}s stance from key-concepts, showing that VAD influence the support and opposition aspects.",
}
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<abstract>Emotion analysis in polarized contexts represents a challenge for Natural Language Processing modeling. As a step in the aforementioned direction, we present a methodology to extend the task of Aspect-based Sentiment Analysis (ABSA) toward the affect and emotion representation in polarized settings. In particular, we adopt the three-dimensional model of affect based on Valence, Arousal, and Dominance (VAD). We then present a Brexit scenario that proves how affect varies toward the same aspect when politically polarized stances are presented. Our approach captures aspect-based polarization from newspapers regarding the Brexit scenario of 1.2m entities at sentence-level. We demonstrate how basic constituents of emotions can be mapped to the VAD model, along with their interactions respecting the polarized context in ABSA settings using biased key-concepts (e.g., “stop Brexit” vs. “support Brexit”). Quite intriguingly, the framework achieves to produce coherent aspect evidences of Brexit’s stance from key-concepts, showing that VAD influence the support and opposition aspects.</abstract>
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%0 Conference Proceedings
%T Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts
%A Vorakitphan, Vorakit
%A Guerini, Marco
%A Cabrio, Elena
%A Villata, Serena
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F vorakitphan-etal-2020-regrexit
%X Emotion analysis in polarized contexts represents a challenge for Natural Language Processing modeling. As a step in the aforementioned direction, we present a methodology to extend the task of Aspect-based Sentiment Analysis (ABSA) toward the affect and emotion representation in polarized settings. In particular, we adopt the three-dimensional model of affect based on Valence, Arousal, and Dominance (VAD). We then present a Brexit scenario that proves how affect varies toward the same aspect when politically polarized stances are presented. Our approach captures aspect-based polarization from newspapers regarding the Brexit scenario of 1.2m entities at sentence-level. We demonstrate how basic constituents of emotions can be mapped to the VAD model, along with their interactions respecting the polarized context in ABSA settings using biased key-concepts (e.g., “stop Brexit” vs. “support Brexit”). Quite intriguingly, the framework achieves to produce coherent aspect evidences of Brexit’s stance from key-concepts, showing that VAD influence the support and opposition aspects.
%R 10.18653/v1/2020.coling-main.19
%U https://aclanthology.org/2020.coling-main.19
%U https://doi.org/10.18653/v1/2020.coling-main.19
%P 219-224
Markdown (Informal)
[Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts](https://aclanthology.org/2020.coling-main.19) (Vorakitphan et al., COLING 2020)
ACL