Automated sentiment analysis
Automated sentiment analysis is a process of using computer algorithms to analyze text and determine the sentiment of the text. This process can be used to analyze customer reviews, social media posts, and other text-based data to gain insights into how people feel about a product, service, or topic.
Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.