Sentiment
Enable this model configuration to analyze speaker sentiment based on spoken text (Lexical Emotion Analysis) is the response inside the sentiment key
Sentiment Analysis will help you interpret and quantify if the conversation in the audio or video is Positive, Very Positive, Negative, Very Negative or Neutral. It also provides you a measure as to how subjective the conversation is with a
subjectivity score.Sentiment | Description | Example |
|---|---|---|
Very Positive | a statement or sentence that is highly positive | "Brilliant work John, you really came through." |
Positive | a statement or a sentence that is marginally positive | "Okay let's hope everything is fine." |
Neutral | a statement or a sentence that is neutral | "..sure I will do that tomorrow" |
Very Negative a statement or sentence that is highly positive | a statement or sentence that is highly negative | "I don't think that will happen today" |
Negative | a statement or a sentence that is marginally Negative |
{
"status": true,
"error": {},
"data": {
"sentence": "At Marsview we build things that change things",
"avgSentiment": "Neutral",
"avgPolarity": 0,
"avgSubjectivity": 0,
"content": [
{
"phrase": "At Marsview we build things that change things",
"sentiment": "Neutral",
"polarity": 0,
"subjectivity": 0
}
]
}
}
status field will be set to false if something went wrong while processing the request check for any error messages in the error fieldField | Description |
|---|---|
avgPolarity | Average Polarity score of the given content. This value ranges between -1 and 1. Where -1 is Very negative and 1 is Very positive |
avgSentiment | Average predicted sentiment of the given content |
avgSubjectivity | Average Subjectivity of the given content |
content | A list of sentences/trascriptions for which sentiment has been predicted. This would typically only have one object for realtime analysis |
phrase | The sentence for which sentiment has been predicted |
polarity | Polarity score of the given content. This value ranges between -1 and 1. Where -1 is Very negative and 1 is Very positive |
sentiment | Predicted sentiment of the given content based on the polarity |
subjectivity | A scale of how much the sentence is based on facts and figures. A high subjectivity indicates that the information given by the speaker is not based on facts and that it is highly subjective. |
sentence | The sentence for which sentiment has been predicted |
Last modified 1yr ago