Sentiment analysis is the process of helping users understand human thoughts and feelings in all types of data using natural language processing (NLP) and machine learning (ML) algorithms. It detects underlying positive, negative or neutral sentiment in text, voice, and video conversations. Different types of sentiment analysis include document-level, sentence-level, aspect-based and contextual sentiment analysis. Aspect-based sentiment analysis categorizes opinions by aspect and identifies the sentiment related to each target, while contextual sentiment analysis recognizes cues and enhances other types of sentiment analysis. Businesses can leverage sentiment analysis data for various uses such as shaping sales and marketing plans, evaluating social media posts, improving crisis management and brand strength. When choosing a Sentiment Analysis API, look for contextual understanding, performance, extensibility, and the ability to surface useful information in real-time. Symbl.ai is an AI-powered platform that offers aspect-based sentiment analysis performed on real-time messages, polarity values, and other valuable conversation analytics. It can be used on both asynchronous audio, video or text data as well as streaming audio or video content. Sentiment analysis can be used for various purposes such as social media listening, analyzing video survey responses, processing employee feedback, identifying unhappy customers, and measuring engagement and empathy in internal and external conversations.