Sentiment analysis is an approach to natural language processing (NLP) that identifies the emotional tone behind a body of text. The digital text is analyzed to determine if the emotional tone of the message is positive, negative, or neutral. Sentiment analysis tools can automatically determine the author’s attitude towards a topic by scanning this text.
Sentiment analysis - opinion mining - is important for business intelligence as it helps companies improve their products and services, as well as increasing brand reputation.
- Fine-Grained Scoring: categorizing the text intent into multiple levels of emotion.
- Example: 5-star rating system
- Aspect-Based: focusing on particular aspects of a product or service.
- Intent-Based: helps understand customer sentiment when conducting market research, picking customers interested in buying with words like discounts, deals, and reviews in monitored conversations.
- Emotional Detection: analyzing the psychological state of a person when they are writing the text.
- interpret emotions include joy, anger, sadness, and regret.
- Sarcasm: may cause ambiguity.
- Negation: the use of negative words to convey a reversal of meaning in the sentence.
- Multipolarity: when a sentence contains more than one sentiment.
Reference: https://aws.amazon.com/what-is/sentiment-analysis/