BrandMentions goes beyond basic positive, negative, neutral sentiment. It uses Artificial Intelligence to detect the specific emotions and tones in your brand mentions, so you can understand not just what people say, but how they feel when they say it.
How AI detects emotions and tones in BrandMentions
BrandMentions emotion and tone detection is powered by AI models trained on large amounts of text from across the web. These models have learned patterns that link language to different feelings and styles.
Here is a simplified view of how it works.
1. The AI reads the text of each mention
For every mention, the AI scans:
Words and phrases
Sentence structure
Punctuation and emphasis, such as exclamation marks or repeated letters
Example:“I absolutely love this update, it is amazing!”
The AI sees strong positive language and emphasis.
2. It looks for emotional and tonal cues
The AI has learned which words and patterns are usually linked to certain emotions or tones.
For example:
Words like “love”, “amazing”, “excellent” often signal joy or enthusiasm
Words like “hate”, “terrible”, “disappointed” often signal anger or frustration
Informal phrases like “lol”, “haha”, or emojis often signal a casual or humorous tone
Phrases that exaggerate or sound exaggerated can signal irony or sarcasm
These cues help the AI estimate what the writer is feeling and how they sound.
3. It considers the context, not only individual words
Words can change meaning depending on the context. The AI does not just count positive or negative words. It reads them in context.
For example:
“That feature is sick” can be positive in a modern, informal context.
“I am sick of this feature” is negative and shows frustration.
The AI model has been trained to understand many of these language patterns and informal uses, including slang and some forms of sarcasm.
4. It assigns emotion and tone labels
After reading the full mention and its context, the AI assigns one or more labels, such as:
Emotions like joy, anger, sadness, frustration, excitement, disappointment
Tones like formal, informal, humorous, sarcastic, neutral
These labels become part of your BrandMentions data and can be used in filters, analysis, and AI generated insights.
How to use emotion and tone insights in practice
Here are some practical ways to use emotion and tone detection in BrandMentions:
Filter mentions by emotion, for example show only angry or frustrated mentions and send them to support.
Run AI Analysis on negative emotion mentions to see main causes and patterns.
Use the AI Assistant to ask:
“What emotions are most common in mentions about our latest release?”
“What tones do our most positive mentions use?”
Track changes over time, for example whether anger is going down after you fix an issue.
By going beyond basic sentiment and using AI to detect emotions and tones, BrandMentions helps you build a deeper, more empathetic understanding of your audience, and turn that understanding into better products, better communication, and better customer relationships.