Sentiment Analysis
Sentiment analysis is the use of language processing to detect whether a text or a spoken comment expresses a positive, negative or neutral opinion, and sometimes the emotion or intensity behind it.
Definition
Sentiment analysis reads a piece of text, such as a review, a survey comment or a transcript, and labels the opinion it expresses. The simplest version gives a polarity: positive, neutral or negative. More detailed versions score intensity, attach a sentiment to each topic mentioned, or try to name an emotion such as frustration or satisfaction.
Results are checked by comparing the tool's labels with those given by people on a sample, and by looking at where they disagree. Irony, negation, mixed feelings, industry jargon and cultural differences are well-known difficulties: “not bad” and “great, another delay” are easy to misread. Analysis of voice tone adds another layer, and is much less reliable than analysis of words.
It is useful for seeing the overall mood across hundreds of comments, or for spotting a theme that is turning negative. It should not be used to judge an individual on their emotional state alone, and inferring emotions about people at work or at school is a sensitive practice in some regulations. Treat scores as a pointer to what to read, not as a verdict.
Key points
- It labels opinion in text as positive, neutral or negative, sometimes with intensity or emotion.
- It works best for trends across many comments.
- Irony, negation and mixed feelings are frequent causes of error.
- Validate it by comparing results with human labels on your own data.
- Do not use it alone to judge an individual; check the rules on emotion inference where you operate.
Example
A support team collects 2,000 comments after customer calls. Sentiment analysis shows that comments about delivery are mostly negative, while comments about the advisors are mostly positive. The team reads fifty of the negative delivery comments to understand what is going wrong before acting.
Frequently asked questions
Is sentiment analysis the same as emotion detection?
Not quite. Sentiment analysis rates opinion as positive or negative, while emotion detection tries to name feelings such as anger or joy. The second is less reliable and more sensitive.
How accurate is it?
It depends on the language, the topic and the quality of the text. It is usually good for clear opinions and weaker for sarcasm or short ambiguous remarks.
Can it replace reading the comments?
No. It helps you decide what to read first and shows overall patterns, but the detail and the reasons are in the comments themselves.
Related terms
AI conversations, human decisions
Passisto holds structured voice conversations with candidates, employees, clients and students, and turns them into reports your team can act on.