Sentiment analysis categorizes text into different emotional tones, such as positive, negative, or neutral, and sometimes into more detailed emotions like anger, happiness, or sadness. Examples of ...

Sentiment Analysis is a branch of Natural Language Processing (NLP) that involves determining the emotional tone or opinion expressed in a piece of text. It is commonly used to analyze social ...

Sentiment analysis uses machine learning techniques like natural language processing (NLP) and other calculations such as biometrics to determine if specific data is positive, negative or neutral.

Sarkar goes on to perform sentiment analysis using several unsupervised methods, since his example data set hasn’t been tagged for supervised machine learning or deep learning training.

Sentiment Analysis is a branch of Natural Language Processing (NLP) that involves determining the emotional tone or opinion expressed in a piece of text. It is commonly used to analyze social media ...

For example, consulting giant Genpact uses sentiment analysis with its 100,000 employees, says Amaresh Tripathy, the company’s global leader of analytics. “We use an AI tool, a conversational ...

Search for Automated Sentiment Analysis, for example, ... can help to uncover some of what might have been missed in the automated analytical process. ... The Role of AI and Open-Text Analysis in ...

Mining Facebook and Twitter posts for clues about customer sentiment is one of the most common big data workloads today. Now, thanks to improvements in the accuracy of speech-to-text algorithms and ...

Sentiment analysis can automatically detect emotions and opinions by classifying the customer's text as positive, negative or neutral through the use of artificial intelligence (AI), natural ...

Sentiment Analysis is a branch of Natural Language Processing (NLP) that involves determining the emotional tone or opinion expressed in a piece of text. It is commonly used to analyze social ...