A Natural Language Processing for Sentiment Analysis from Text using Deep Learning Algorithm

Sentiment analysis has its large application in a natural language processing. Natural language processing have a large range of applications like machine translation, aspect-oriented product analysis, product reviews, text classification and sentiment analysis for spam filtering and email categorization. Lexicons are widely used in emotion detection systems can be defined as a list of words that the emotions convey or complex machine learning algorithms. In this implementation, BERT (Bidirectional Encoder Representations for Transformers) is used as a deep learning-based unsupervised method for natural language processing that enables computers to understand text representations in terms of context when performing tasks like question-answering, language inference, and text summarization. The suggested method divides the text into various emotional states, such as neutral, sadness, fear, joy, anger, etc.