Aspect Based Sentiment Analysis

Aspect-Based Sentiment Analysis (ABSA) is a task in natural language processing aimed at identifying and extracting the sentiment of specific aspects of products or services. ABSA involves a multi-step process: first, it identifies the aspects of the product or service being discussed in the text, then performs sentiment analysis to assign an emotional polarity (positive, negative, or neutral) to each aspect based on the context of the sentence or document. Finally, the results are aggregated to provide an overall sentiment for each aspect. In recent years, research has proposed more complex ABSA tasks, such as predicting sentiment triplets or quadruplets, including Aspect-Sentiment Term Extraction (ASTE), Target Aspect Sentiment Detection (TASD), Aspect-Sentiment Quadruple Prediction (ASQP), and Aspect-Opinion Co-occurrence Selection (ACOS), with a focus on implicit aspects or opinions.