Papers with Aspect based sentiment analysis

3 papers
Aspect Based Sentiment Analysis with Gated Convolutional Networks (P18-1)

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Challenge: Aspect-based sentiment analysis can provide more detailed information than general sentiment analysis.
Approach: They propose a model based on convolutional neural networks and gating mechanisms which can selectively output the sentiment features according to the given aspect or entity.
Outcome: The proposed model can selectively output sentiment features according to the given aspect or entity.
Aspect Sentiment Classification with Aspect-Specific Opinion Spans (2020.emnlp-main)

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Challenge: Existing attention-based models for sentiment analysis are not able to capture opinion spans as a whole or variable-length opinion span.
Approach: They propose a model that extracts aspect-specific opinion spans and evaluates sentiment polarity by exploiting extracted opinion features.
Outcome: The proposed model extracts aspect-specific opinion spans and evaluates sentiment polarity using extracted opinion features.
A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis (D19-1)

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Challenge: Existing models use aspect-independent encoders for sentence representation generation.
Approach: They propose an aspect-guided deep transition model which guides the sentence encoding from scratch with a specially-designed deep transition architecture.
Outcome: The proposed model outperforms existing models on multiple datasets on aspect-category sentiment analysis and aspectterm sentiment analysis without additional features.

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