Specific numerical scores returned by emotion analysis (e.g., sadness score, joy score, fear score, disgust score, anger score).
Emotion Scores are specific numerical outputs provided by the Emotion Analysis module of APIs like IBM Watson NLU. These scores quantify the intensity of specific emotions detected in the text.
The emotions measured include sadness, joy, fear, disgust, and anger. The resulting numerical data (e.g., sadness score, joy score) is then used to calculate custom classification fields in visualization tools like Looker Studio, such as the “Category Label (Emotion)” which categorizes the emotion based on score thresholds.
Sources & References
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A
Accuracy Score
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B
Bounce Rate
A GA4 user engagement metric used to monitor patterns in user interaction.
C
Coherence Score
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C
Confidence Score (Generative AI)
A measure of certainty provided by a generative AI model regarding its classification.
C
CPC (Cost Per Click)
A metric used in keyword analysis and visualizations.
C
CTR (Click-Through Rate)
A metric related to user interaction with search results.
E
Entity Salience Score
A score assigned by the Google Natural Language API to each extracted entity, indicating its…
K
Keyword Difficulty (KD)
A metric associated with keywords, used in prioritization and visualization.
Q
Query Distance
A measure of how similar queries are to one another, often calculated using fuzzy matching.
S
Salience (Importance)
A metric indicating the importance or prominence of an entity in the context of the…
S
Search Volume (Volume)
A traditional keyword metric, referring to the monthly search volume, used in analysis and prioritization.
S
Sentiment Magnitude
A metric returned by the Google Natural Language API alongside Sentiment Score, used in entity…
