Published Paper Details:

Sentiment analysis is the process of analyzing online conversations like tweets, blog posts, or comments to understand people's opinions about specific topics or services. It categorizes these opinions as positive, negative, or neutral, helping businesses assess customer sentiment regarding their products.Aspect-Based Sentiment Analysis (ABSA) takes this a step further by identifying specific features or aspects of a product mentioned in customer reviews. It also determines whether the sentiment about each aspect is positive, negative, or neutral. This detailed feedback helps businesses focus on improving specific product features based on customer opinions, making their products more appealing and successful.The proposed method for ABSA uses BERT, a powerful pre-trained language model, to better understand the context in reviews. By fine-tuning BERT on data specific to a particular domain and using techniques that address multiple tasks at once (like extracting aspects and classifying sentiment), this approach improves the accuracy of ABSA. It is especially effective at handling complex language and understanding relationships between different aspects in reviews.