How Our Technology Works
Transform broadcast language into actionable insights
Our platform combines semantic analysis with advanced sentiment detection to decode the true impact of media coverage. While semantic analysis uncovers the underlying meaning and themes of a broadcast, sentiment analysis captures its emotional tone. Together, they provide a comprehensive understanding of not just what was said, but the context and framing behind every mention.
Automation is the key to scalability. Manual labelling and interpretation are time-consuming and too slow for today’s media cycle; our automated deduplication and intelligent processing eliminate noise, ensuring your team focuses only on unique, high-value insights.
Semantic Analysis
Go beyond keywords.
- Topic-Level Monitoring: Capture high-level semantics that humans grasp naturally. Our monitoring reflects the true meaning and context of a broadcast, not just exact keyword matches.
- Redundancy Reduction:Intelligently detect when the same content appears multiple times across different channels, significantly reducing noise and duplication in your feed.
Named Entity Detection
Identify the “who/what/where” automatically.
- Automated Labelling: Instantly detect and label key entities—including people, organizations, and locations—within broadcast-derived text to enhance discovery and filtering.
- Structured Intelligence: Transform unstructured mentions into structured data that is easier to search, report on, and integrate directly into your BI tools.
Story Segmentation and Topic Detection
Turn continuous streams into manageable stories.
- Topical Segmentation: Continuous broadcast content is automatically divided into coherent, topic-based segments, making it significantly easier to review and analyse.
- Editorial Workflow Support: Work by story instead of raw timestamps; enabling faster triage, logical grouping, and structured reporting.
Sentiment Analysis
Understand the tone, not just the facts.
- Emotional Context: Add the critical emotional layer—positive, negative, or neutral framing to help prioritize what truly requires attention.
- Context + Tone Together: Combine sentiment with semantic and topic detection to understand not only what a story is about, but how it is being presented.
- Faster Review Cycles: Auto-generated headlines and summaries, enriched with sentiment insights, accelerate editorial workflows and decision-making.
Book a demo
Ready to see semantic and sentiment analysis applied to your topics?
Share your brands, spokespeople, and key themes with us. In a live demo, we will show you exactly how eMM surfaces topics, identifies entities, segments stories, and applies sentiment analysis to provide a complete picture of your media presence.
Book a demo
Find more information about the other technologies used by eMM:
> Audio Processing
> Video Processing
> Real Time
