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Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts

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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.
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Dates and versions

hal-03031812 , version 1 (30-11-2020)

Identifiers

  • HAL Id : hal-03031812 , version 1

Cite

Vorakit Vorakitphan, Marco Guerini, Elena Cabrio, Serena Villata. Regrexit or not Regrexit: Aspect-based Sentiment Analysis in Polarized Contexts. COLING'2020 - 28th International Conference on Computational Linguistics (COLING'2020), Dec 2020, Barcelona / Online, Spain. ⟨hal-03031812⟩
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