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

2020-12-01 · COLING 2020 8 · Vorakit Vorakitphan, Marco Guerini, Elena Cabrio, Serena Villata

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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Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Emotion RecognitionSentenceSentiment Analysis

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