In recent years, Aspect-based Sentiment Analysis (ABSA) has been a crucial yet challenging
task in recognizing textual emotions from text. ABSA has numerous application across …

Aspect-based Sentiment Analysis (ABSA) is a type of fine-grained sentiment analysis (SA)
that identifies aspects and the associated opinions from a given text. In the digital era, ABSA …

Abstract Aspect-based Sentiment Analysis (ABSA) is used to detect corresponding
sentiment polarities toward different aspect terms. In recent years, graph convolutional …

Recently, aspect-based sentiment analysis (ABSA) models have yielded promising results.
However, they are susceptible to learning spurious correlations between certain words of …

Natural Language Generation (NLG) acts as a bridge between input data and human
communication. NLG systems are meant to generate human-understandable output making …

The Language Model Models (LLMs) have demonstrated their ability to process and
understand natural language inputs accurately. This indicates that LLMs are capable of …

Introduction: Aspect-based sentiment classification is a fine-grained sentiment classification
task. State-of-the-art approaches in this field leverage graph neural networks to integrate …

In addition to a large amount of text, there are also many emoticons in the comment data on
social media platforms. The multimodal nature of online comment data increases the …

Given that emotional content spreads more widely than rational content in social networks,
as well as the complexity of user cognition and the interaction of derivative topics, this paper …

Aspect-based sentiment analysis is a challenging yet critical task for recognizing emotions in
text, with various applications in social media, commodity reviews, and movie comments …