Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture
The World Wide Web holds a wealth of information in the form of unstructured texts such as customer reviews for products, events and more. By extracting and analyzing the expressed opinions in customer reviews in a fine-grained way, valuable opportunities and insights for customers and businesses can be gained. We propose a neural network based system to address the task of Aspect-Based Sentiment Analysis to compete in Task 2 of the ESWC-2016 Challenge on Semantic Sentiment Analysis. Our proposed architecture divides the task in two subtasks: aspect term extraction and aspect-specific sentiment extraction. This approach is flexible in that it allows to address each subtask independently. As a first step, a recurrent neural network is used to extract aspects from a text by framing the problem as a sequence labeling task. In a second step, a recurrent network processes each extracted aspect with respect to its context and predicts a sentiment label. The system uses pretrained semantic word embedding features which we experimentally enhance with semantic knowledge extracted from WordNet. Further features extracted from SenticNet prove to be beneficial for the extraction of sentiment labels. As the best performing system in its category, our proposed system proves to be an effective approach for the Aspect-Based Sentiment Analysis.
Code (0)
등록된 구현이 없습니다.
Tasks
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Sentiment AnalysisTask 2Term ExtractionVocal Bursts Valence PredictionSimilar Papers 제목 키워드 기반
Joint Aspect Extraction and Sentiment Analysis with Directional Graph Convolutional Networks
End-to-end aspect-based sentiment analysis (EASA) consists of two sub-tasks: the first extracts the aspect terms in a sentence and the second predicts the sentiment polarities for such terms. For EASA, compared to pipeli…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect ExtractionSentence+1IARM: Inter-Aspect Relation Modeling with Memory Networks in Aspect-Based Sentiment Analysis
Sentiment analysis has immense implications in e-commerce through user feedback mining. Aspect-based sentiment analysis takes this one step further by enabling businesses to extract aspect specific sentimental informatio…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Extract AspectGeneral Classification+3Aspect-Based Relational Sentiment Analysis Using a Stacked Neural Network Architecture
Sentiment analysis can be regarded as a relation extraction problem in which the sentiment of some opinion holder towards a certain aspect of a product, theme or event needs to be extracted. We present a novel neural arc…
RelationRelation ExtractionSentiment AnalysisTerm ExtractionVarious Approaches to Aspect-based Sentiment Analysis
The problem of aspect-based sentiment analysis deals with classifying sentiments (negative, neutral, positive) for a given aspect in a sentence. A traditional sentiment classification task involves treating the entire se…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)General ClassificationSentence+2SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis
Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and research applications. In high-resource languages, this has been ext…
Sentiment Analysis