Knowledge Discovery 25.2
Knowledge Discovery Expert

# Sentiment Analysis

Linguistic sentiment analysis (LSA) is a tool based on Named Entity Recognition that you can use to identify positive or negative sentiments in text. Sentiment analysis is available as Named Entity Recognition grammar files, in various major languages.

The sentiment analysis grammar files define positive and negative sentiments. Some of them have components defined, which allow you to extract attributes from matched phrases, such as topic, subject, and positive or negative sentiments.

## The Sentiment Analysis Grammars

Named Entity Recognition matches input data to patterns defined with regular expressions (Grammars).

The sentiment analysis grammar first defines dictionaries with the parts of speech. There are different dictionaries for positive and negative words, and other categories that describe different effects on the sentiment, where appropriate.

These dictionaries are combined to form simple phrases that convey positive or negative sentiments. Finally, these phrases are padded, usually with other phrases, to form various patterns for the final entities, which match strings from the text that express positive or negative sentiment.

The grammar files are designed to be used out of the box. You just need to load the appropriate grammar file, and optionally choose the entities (usually positive or negative) to match with.

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Version 25.2 | Last updated April 2025

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Product: Knowledge Discovery 25.2

Topic Title: Sentiment Analysis