Sentiment vs. Emotion Analysis Analysis

What is the difference between feelings (positive and negative) and emotions in word processing (NLP)? For example, anger is a negative emotion, but negative feelings seem to be the same. Vijay Nadadur, creator of SentiRank, an algorithm that evaluates sentiment in text, suggests Bio Positions can be expressed mostly in binary (+ ve and -ve) in a simplified way. To add further, you can have varying degrees of + ve and -ve sentiment, and possibly neutral. However, emotions are multidimensional. Rage is for sure a feeling and it is sadness, but they are not really the same.

To talk more specifically about text mining (based on NLP), it is much easier to do sentiment analysis, but it is very difficult to do emotional analysis. The next level of sentiment analysis is intent analysis, where few researchers have worked to find intent from a chunk of text, which seems like a very high business value.


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Emotions could be viewed as a finer granularity. As you say in the question itself, “anger” and “sadness” are also negative feelings, but of course they are different emotions. Thus, the analysis of emotions can be done as an additional layer on top of the (relatively) simple classification of feelings.

================================================== ==============================
| Sentiment Polarity | 10 Emotion Classes | Emotion word examples |
| ------------------------------------------------- ---------------------------- |
| | Happiness | happy, joyful, glad |
| Positive | Pleasantness | pleasant, enjoy, nice |
| | Relief | relief, comfort, solace |
| ------------------------------------------------- ---------------------------- |
| | Fear | scare, fear, frightening |
| | Sadness | sad, grief, mourn |
| | Disappointment | bummer, regret, dejected |
| Negative | Unpleasantness | dislike, yuck, irksome |
| | Loneliness | lonely, withdrawn |
| | Anxiety | anxiety, worry, distress |
| | Anger | anger, furious, antagonize |
================================================== ==============================

Note that while the classification of feelings can be binary, triple, or graded (depending on whether + ve or -ve mood), the classification of emotions is much more open to interpretation. For example, one could add love as a positive emotion and hate as a negative emotion. However, keep in mind that as the number of classes increases, creating an accurate classifier becomes more difficult. You may have to start thinking about soft clustering approaches because the boundary between two emotions can be unclear (not just AI, sometimes even humans don't understand it!).



It's also called: Predicting Someone's Mood Swings.

I think Freud would say that emotions are associated with the flow of libido (body and soul), while feelings also have a cultural and moral dimension. Feeling is already a sublimation of emotions, it is an expression of emotions, as in the table below in response 1. We feel joy, joy, fear, angry, and we express it in words or behavior.

Negative libido streams cause anger / sadness or joy / happiness. + ve and -ve change occurs when external events affect our psychological balance and cause either increased happiness or decreased happiness. If you know these events and can relate them to mood expressions, you can measure the degree of change in emotions. The latter depends on the importance of the event in connection with the personal setting of the personality (culture, education, psychological attitude).

In the context of data mining and looking for intent: If you want to find or even customize the measure of intent, you need to find events that trigger patterns in expressions and user behavior. It is like looking for clusters of expressions associated with a person who has emotions and a certain time, and associate them with external events. Like many people, he is sad or angry about the terrorist attacks.

In addition, people can actually express feelings that conflict with their emotions. This can only be appreciated if you know the cultural / psychological setting.



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