Analyze sentiment to view a speaker's expressed feeling or enthusiasm about a specific topic.

To analyze sentiment, combines the Conversations API Speech-to-Text messages, usually sentences, with Topics. For a given conversation, the Topics algorithm analyzes each message and provides a sentiment polarity score (-1.0 to +1.0) and suggest a sentiment type of positive, neutral, or negative.


Before using this API, generate your authentication token (AUTH_TOKEN) as described in Authenticate.

Speech-to-text and topics requests

Start by processing a conversation. The result is a conversation ID and a raw transcript.

Pass the conversation ID in a Get members request. The response is a transcript formatted to support conversation intelligence.

Pass the conversation ID in a Get topics request, with parameter sentiment=true.

For Topics level analysis, the sentiment algorithm analyzes the messages and factors in the sentiment for each topic.

API responses

    "messages": [
             "id": "6412283618000896",
             "text": "Best package for you is $69.99 per month.",
             "from": {
                 "name": "Roger",
                 "email": "[email protected]"
             "startTime": "2020-07-10T11:16:21.024Z",
             "endTime": "2020-07-10T11:16:26.724Z",
             "conversationId": "6749556955938816",
             "phrases": [
                    "type": "action_phrase",
                    "text": "$69.99 per month"
             "sentiment": {
                "polarity": {
                    "score": 0.6
        }       ]
    "topics": [
            "id": "5907389282779136",
            "text": "interns",
            "type": "topic",
            "score": 0.7178597920690242,
            "messageIds": [
            "sentiment": {
                "polarity": {
                    "score": 0.389
                "suggested": "positive"
            "parentRefs": []
        }     ]


polarityThe intensity of the sentiment. Intensity ranges from -1.0 to 1.0, where -1.0 is the most negative sentiment and 1.0 is the most positive sentiment.
suggestedDisplay the suggested sentiment type of negative, neutral, or positive.

Suggested sentiment

The sentiment polarity ranges and suggested sentiment types cover a wide range of conversations.

Polarity may vary for your use case. Define a threshold that works for your environment. Then adjust the threshold after testing and verifying results.

PolaritySuggested Sentiment
-1.0 => x < -0.3negative
-0.3 => x <= 0.3neutral
0.3 > x <= 1.0positive