Sentiment analysis helps you determine these customer sentiments. In this post, we’ll discuss what is sentiment analysis, along with the algorithms used to perform sentiment analysis.

Sentiment analysis is essential for algorithmic trading success. It provides insights into market sentiment, enhances predictive capabilities, and helps in risk mitigation. Continuous learning and ...

Intel’s AI lab has released an open-source version of a sentiment analysis algorithm designed to boost natural language processing applications that currently lack the ability to scale across ...

Sentiment analysis algorithms can struggle with subjectivity, especially when the sentiment expressed is subtle or nuanced. Accuracy Issues: Many sentiment analysis tools are prone to errors when ...

However, sentiment analysis is also being used in unexpected ways. In what could be a game-changer for marketers, the power of these algorithms can be brought to bear on a range of predictive tasks.

Sentiment analysis is a technique used to figure out the emotional tone behind words. It tells you whether someone’s opinion is positive, negative, or neutral. Sentiment analysis helps machines ...

These days, sentiment analysis relies largely on supervised or semi-supervised machine learning algorithms. All the big cloud players offer sentiment analysis tools, as do most major customer ...

The global market for Sentiment Analytics was valued at US$5.1 Billion in 2024 and is projected to reach US$11.4 Billion by 2030, growing at a CAGR of 14.3% from 2024 to 2030. This comprehensive ...