It is Simple Sometimes: A Study On Improving Aspect-Based Sentiment Analysis Performance
Aspect-Based Sentiment Analysis (ABSA) involves extracting opinions from textual data about specific entities and their corresponding aspects through various complementary subtasks. Several prior research has focused on developing ad hoc designs of varying complexities for these subtasks. In this paper, we present a generative framework extensible to any ABSA subtask. We build upon the instruction tuned model proposed by Scaria et al. (2023), who present an instruction-based model with task descriptions followed by in-context examples on ABSA subtasks. We propose PFInstruct, an extension to this instruction learning paradigm by appending an NLP-related task prefix to the task description. This simple approach leads to improved performance across all tested SemEval subtasks, surpassing previous state-of-the-art (SOTA) on the ATE subtask (Rest14) by +3.28 F1-score, and on the AOOE subtask by an average of +5.43 F1-score across SemEval datasets. Furthermore, we explore the impact of the prefix-enhanced prompt quality on the ABSA subtasks and find that even a noisy prefix enhances model performance compared to the baseline. Our method also achieves competitive results on a biomedical domain dataset (ERSA).
Code (1)
Tasks
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Sentiment AnalysisMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Aspect Based Sentiment Analysis with Self-Attention and Gated Convolutional Networks
Aspect based sentiment analysis (ABSA) is a fine-grained sentiment analysis task, whose main goal is to identify the sentiment polarity of an aspect in a sentence. A sentence may contain many different aspects, each of w…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect Category Sentiment AnalysisSentence+1Aspect-Based Sentiment Analysis Techniques: A Comparative Study
Since the dawn of the digitalisation era, customer feedback and online reviews are unequivocally major sources of insights for businesses. Consequently, conducting comparative analyses of such sources has become the de f…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Sentiment AnalysisAttention Transfer Network for Aspect-level Sentiment Classification
Aspect-level sentiment classification (ASC) aims to detect the sentiment polarity of a given opinion target in a sentence. In neural network-based methods for ASC, most works employ the attention mechanism to capture the…
ClassificationGeneral ClassificationSentenceSentiment Analysis+1A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) has attracted increasing attention recently due to its broad applications. In existing ABSA datasets, most sentences contain only one aspect or multiple aspects with the same sentim…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)SentenceSentiment AnalysisCAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis
Aspect level sentiment classification is a fine-grained sentiment analysis task. To detect the sentiment towards a particular aspect in a sentence, previous studies have developed various attention-based methods for gene…
General ClassificationSentenceSentiment AnalysisSentiment Classification