What is Eureka AI?
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Eureka AI transforms data management by combining real-time feedback and business records from all sources while providing excellent security with user access control, name anonymization, and ISO 27001 certification. It uses Feedier's query language with 20+ filters for fast and accurate data searches. Built on cutting-edge LLM technology, Eureka AI delivers precise text insights and information retrieval. |
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Sentiment | Explanation | Sentiment rate average |
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| The verbatim is linked to a positive emotion on the part of the customer: Joy, Confidence, Serenity, Admiration. | [95%-100%]97.5% |
😐 | The verbatim is not directly linked to an emotion or the emotion is not expressed strongly enough to be categorised. | 50% |
😠 | The verbatim is linked to a negative emotion on the part of the customer: Anger, Contempt, Sadness, Disgust. | [1%-5%] |
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2.5% |
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How is the sentiment rate score calculated for a themetopic? This is the total average of the sentiment scores for each verbatim related to a theme. |
Here are a few examples:
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Number of positives
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10
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10
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15
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5
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😐 Number of neutrals
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0
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10
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10
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10
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😠 Number of negatives
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0
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10
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5
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10
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Sentiment rate
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~ 100%
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~ 50%
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~ 66%
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of verbatim related to a topic. Formula:  Sentiment score ranges:
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In the Text analysis module you have an individual sentiment score for each topic and can view a breakdown of the sentiment score.
So let's dig into an example, What is the issue has 20 answers with the following breakdown:
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As explained earlier, each answer has a sentiment rate so to calculate the average we do:
[20% * 97.5%] + [0% * 50%] + [ 80% * 2.5%] = 21.8% which leads to an overall negative sentiment score
Lets dive into further examples.
As a user you have 3 different topics which have the following breakdown:
| 😐 Neutral Answers | 😠 Negative Answers | Sentiment Score | |
Topic 1: Improvements | 30% | 40% | 30% | 49% → Neutral |
Topic 2: Facilities | 71% | 18% | 11% | 78% → Positive |
Topic 3: Management | 20% | 0% | 80% | 21.8% → Negative |
Type 2 : Entity detection
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