Sentiment analysis estimates whether whether a piece of text is negative, neutral or positive.
There are two approaches towards sentiment analysis: binary or polarity based or intensity/valence based.
The polarity based only provides information if a certain text is postive or negative.
For example, 'good' and 'perfect' would score the same.
In contrast, a valence based sentiment analysis also takes the intensity of a word into account, therefore giving a higher value to 'perfect' in the example above.
One of the major applications of sentiment analysis is judge social media streams (Twitter, facebook posts).
For example, companies use it to identify negative feedbacks on social media and react/answer to them.
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