BrandMentions uses a powerful Artificial Intelligence (AI) engine to automatically detect and interpret the sentiment behind every online mention of your brand. This AI-driven approach goes far beyond basic keyword matching, it understands the context, tone, and intent behind language.
By combining Machine Learning (ML) and Natural Language Processing (NLP), BrandMentions accurately identifies whether a mention expresses a positive, negative, or neutral sentiment. It’s designed to handle the nuances of human communication, including sarcasm, irony, and industry-specific terminology, giving you a reliable view of how people truly feel about your brand.
The Core of the AI: Machine Learning and NLP
Machine Learning (ML)
At the core of BrandMentions’ sentiment engine lies Machine Learning, trained on millions of real-world text samples from across the web. Each sample is labeled according to its sentiment - positive, negative, or neutral - allowing the system to recognize complex patterns, tone shifts, and linguistic cues.
Through this process of supervised learning, the model develops the ability to predict sentiment for new mentions with remarkable accuracy. It doesn’t just look for keywords - it understands how people actually express opinions.
Natural Language Processing (NLP)
NLP enables the AI to understand and interpret language the way humans do. It breaks down each mention into grammatical and semantic components to interpret meaning, tone, and relationships between words.
Here’s how NLP enhances sentiment accuracy:
Recognizes Negation: Understands that “This is not a good product” expresses negativity, even though the word good is present.
Identifies Modifiers: Detects intensity differences between “good,” “very good,” and “exceptionally good,” attributing stronger positivity to more intense expressions.
Understands Context: Considers surrounding text to clarify meaning. For example:
“The battery life is short” → negative.
“It was a short wait for customer service” → positive.
This contextual understanding ensures precise, human-like sentiment interpretation across different tones and situations.
Continuous Improvement
The BrandMentions AI continuously evolves through ongoing learning and user feedback. Each time new data is analyzed, the model refines its understanding of language and sentiment trends.
When you manually adjust the sentiment of a mention, your feedback contributes to the system’s continuous improvement loop, helping the AI become even smarter and more accurate over time.
Customization for Your Brand
Every industry speaks its own language and BrandMentions helps your AI understand yours.
You can create custom instructions in your project settings to teach the system how to interpret specific slang, acronyms, or professional terms.
For example, a healthcare brand might add disease names to a negative list, while a gaming brand could flag slang like “sick” or “killer” as positive. This customization ensures your sentiment analysis reflects your unique brand voice and audience context.
In Short
BrandMentions combines AI intelligence, linguistic expertise, and customization to help you truly understand how your audience feels about your brand — with precision, context, and continuous improvement at its core.