Fine-Grained Opinion Analysis
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Benchmarks
MPQA
Most implemented
Opinion Mining Using Pre-Trained Large Language Models: Identifying the Type, Polarity, Intensity, Expression, and Source of Private States
Mastering the Explicit Opinion-role Interaction: Syntax-aided Neural Transition System for Unified Opinion Role Labeling
Papers
Annotation Quality in Aspect-Based Sentiment Analysis: A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Model
Aspect-Based Sentiment Analysis (ABSA) enables fine-grained opinion analysis by identifying sentiments toward specific aspects or targets within a text. While ABSA has been widely studied for English, research on other l…
Aspect Category Sentiment AnalysisFine-Grained Opinion AnalysisLarge Language Models as Automatic Annotators and Annotation Adjudicators for Fine-Grained Opinion Analysis
Fine-grained opinion analysis of text provides a detailed understanding of expressed sentiments, including the addressed entity. Although this level of detail is valuable, annotating opinions in datasets for model traini…
Aspect Sentiment Triplet ExtractionFine-Grained Opinion AnalysisPrompt EngineeringData AugmentationTowards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models
We propose a scalable method for constructing a temporal opinion knowledge base with large language models (LLMs) as automated annotators. Despite the demonstrated utility of time-series opinion analysis of text for down…
Fine-Grained Opinion AnalysisPrompt EngineeringQuestion AnsweringOpinion MiningOpinion Mining Using Pre-Trained Large Language Models: Identifying the Type, Polarity, Intensity, Expression, and Source of Private States
Opinion mining is an important task in natural language processing. The MPQA Opinion Corpus is a fine-grained and comprehensive dataset of private states (i.e., the condition of a source who has an attitude which may be …
Fine-Grained Opinion AnalysisOpinion MiningSentiment AnalysisSentiment ClassificationFine-Grained Opinion Summarization with Minimal Supervision
Opinion summarization aims to profile a target by extracting opinions from multiple documents. Most existing work approaches the task in a semi-supervised manner due to the difficulty of obtaining high-quality annotation…
Fine-Grained Opinion AnalysisOpinion SummarizationSentiment AnalysisMastering the Explicit Opinion-role Interaction: Syntax-aided Neural Transition System for Unified Opinion Role Labeling
Unified opinion role labeling (ORL) aims to detect all possible opinion structures of 'opinion-holder-target' in one shot, given a text. The existing transition-based unified method, unfortunately, is subject to longer o…
Fine-Grained Opinion Analysis