Span Detection for Aspect-Based Sentiment Analysis in Vietnamese
Aspect-based sentiment analysis plays an essential role in natural language processing and artificial intelligence. Recently, researchers only focused on aspect detection and sentiment classification but ignoring the sub-task of detecting user opinion span, which has enormous potential in practical applications. In this paper, we present a new Vietnamese dataset (UIT-ViSD4SA) consisting of 35,396 human-annotated spans on 11,122 feedback comments for evaluating the span detection in aspect-based sentiment analysis. Besides, we also propose a novel system using Bidirectional Long Short-Term Memory (BiLSTM) with a Conditional Random Field (CRF) layer (BiLSTM-CRF) for the span detection task in Vietnamese aspect-based sentiment analysis. The best result is a 62.76% F1 score (macro) for span detection using BiLSTM-CRF with embedding fusion of syllable embedding, character embedding, and contextual embedding from XLM-RoBERTa. In future work, span detection will be extended in many NLP tasks such as constructive detection, emotion recognition, complaint analysis, and opinion mining. Our dataset is freely available at https://github.com/kimkim00/UIT-ViSD4SA for research purposes.
Code (1)
Tasks
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Emotion RecognitionOpinion MiningSentiment AnalysisSentiment ClassificationVietnamese Aspect-Based Sentiment AnalysisSimilar Papers 제목 키워드 기반
Span Detection for Vietnamese Aspect-Based Sentiment Analysis
SA2SL: From Aspect-Based Sentiment Analysis to Social Listening System for Business Intelligence
In this paper, we present a process of building a social listening system based on aspect-based sentiment analysis in Vietnamese from creating a dataset to building a real application. Firstly, we create UIT-ViSFD, a Vie…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)General ClassificationSentiment Analysis+4ViTOED: A Dataset for Target-Oriented Emotion Detection on Vietnamese Social Media Texts
This paper introduces ViTOED, a novel dataset for target-oriented emotion detection in Vietnamese social media texts. The ViTOED comprises 10,985 user comments and 21,244 manually annotated opinion quadruples (source, ta…
Relation ExtractionNew Benchmark Dataset and Fine-Grained Cross-Modal Fusion Framework for Vietnamese Multimodal Aspect-Category Sentiment Analysis
The emergence of multimodal data on social media platforms presents new opportunities to better understand user sentiments toward a given aspect. However, existing multimodal datasets for Aspect-Category Sentiment Analys…
Aspect Category Sentiment AnalysisMultimodal Sentiment AnalysisSentiment AnalysisVietnamese Datasets+3Investigating Monolingual and Multilingual BERTModels for Vietnamese Aspect Category Detection
Aspect category detection (ACD) is one of the challenging tasks in the Aspect-based sentiment Analysis problem. The purpose of this task is to identify the aspect categories mentioned in user-generated reviews from a set…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect Category DetectionSentiment Analysis