The increasing volume of user-generated content on the web has made sentiment analysis
an important tool for the extraction of information about the human emotional state. A current …

With the constantly growing number of reviews and other sentiment-bearing texts on the
Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …

Universally modeling all typical information extraction tasks (UIE) with one generative
language model (GLM) has revealed great potential by the latest study, where various IE …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Sentiment analysis has been a hot research topic in natural language processing and data
mining fields in the last decade. Recently, deep neural network (DNN) models are being …

Aspect-based sentiment analysis is a fine-grained sentiment analysis task, which needs to
detection the sentiment polarity towards a given aspect. Recently, graph neural models over …

Due to their inherent capability in semantic alignment of aspects and their context words,
attention mechanism and Convolutional Neural Networks (CNNs) are widely applied for …

Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity
towards a specific aspect, is a challenging subtask of sentiment analysis (SA). In this paper …