SentimentViz: Leveraging RoBERTa in Python for Advanced Sentiment Analysis and Visualization in the FMCG Sector

In a data-driven world where governments and businesses seek insights from vast amounts of unstructured text data, sentiment analysis plays a pivotal role in decision-making. Sentiment analysis helps analyze cus-tomer experience, ultimately helping manage customer engagement. To build on this need for deeper sentiment understanding and scalable solutions, SentimentViz is an accelerator that leverages Python and chooses the best methodology for text-mining problems. It enables real-time analysis with robust visualization capabilities. In this study, the Sentiment Viz accelerator is leveraged to estimate the sentiment of 9 different Patanjali prod-ucts using a strong data science framework and best-of-the-class ML techniques. This accelerator can predict sentiment for various products and services, categorizing them as positive, negative, or neutral. Once deployed, it enables real-time sentiment mapping for any product or service.