Itqualityassurance
- What is sentiment analysis in data mining?
- How do you collect data for sentiment analysis?
- What is an example of sentiment analysis?
What is sentiment analysis in data mining?
Sentiment analysis, also referred to as opinion mining, is an approach to natural language processing (NLP) that identifies the emotional tone behind a body of text. This is a popular way for organizations to determine and categorize opinions about a product, service, or idea.
How do you collect data for sentiment analysis?
There are ten main sources from which relevant sentiment analysis data can be gathered for analyzing sentiment. These include news, public information, social media, customer reviews, customer service call center data, employee interaction data, electronic health records, and more. Let's review them in detail.
What is an example of sentiment analysis?
Sentiment analysis studies the subjective information in an expression, that is, the opinions, appraisals, emotions, or attitudes towards a topic, person or entity. Expressions can be classified as positive, negative, or neutral. For example: “I really like the new design of your website!” → Positive.
