TEXT CLASSIFICATION INTO EMOTIONAL STATES USING BERT TECHNIQUE

Sentiment analysis is now regarded as one of the most crucial fields of study within Natural Language Processing (NLP), as customers, business owners, and other stakeholders can benefit from knowing the implicit or explicit attitudes conveyed in social media contents. The term “aspect-based sentiment analysis” (ABSA) was created to capture aspect attitudes stated towards particular review features because researchers realized that the generic sentiments derived from the textual contents were insufficient.. Put forth a transfer learning-based strategy to address the aforementioned issues with current ABSA techniques. To thoroughly assess the suggested methodologies, we create an experiment that uses data from many fields.