Context-Guided BERT for Targeted Aspect-Based Sentiment Analysis

Understand

Aspect-based sentiment analysis (ABSA) and Targeted ASBA (TABSA) allow finer-grained inferences about sentiment to be drawn from the same text, depending on context.

• For example, a given text can have different targets (e.g., neighborhoods) and different aspects (e.g., price or safety), with different sentiment associated with each target-aspect pair.
• In this paper, we investigate whether adding context to self-attention models improves performance on (T)ABSA.
• We propose two variants of Context-Guided BERT (CG-BERT) that learn to distribute attention under different contexts.