AI, Data & Intelligence
Sentiment Analysis
Engineering sentiment analysis engines to track brand perception, customer emotion and product feedback across channels.
Capability overview
What sentiment analysis involves
Sentiment analysis measures the emotional tone behind human text communications, evaluating sentiment as positive, negative or neutral. We construct fine-grained sentiment analysis models and Aspect-Based Sentiment Analysis (ABSA) engines.
Our models evaluate overall document sentiment while extracting explicit sentiment scores for specific product features, pricing, delivery speed and customer support interactions.
We enable brand managers and customer success teams to identify unhappy clients early and protect enterprise reputation.
Throughout the sentiment analysis engagement, our engineering team works alongside your internal stakeholders to establish custom operational workflows, clear delivery milestones and automated validation gates. We focus on aspect-based sentiment analysis (absa) and real-time social & brand monitoring, ensuring that every component is documented, secure and aligned with your broader technology strategy.
What is included
What the engagement covers
Aspect-Based Sentiment Analysis (ABSA)
Extracting granular sentiment scores for specific product features (e.g., battery life, software stability).
Real-Time Social & Brand Monitoring
Tracking live social media channels, news outlets and forum discussions for sudden negative sentiment spikes.
Customer Support Emotion Tracking
Detecting customer frustration, urgency and tone changes across support ticket exchanges.
Product Review & NPS Analysis
Correlating Net Promoter Scores (NPS) with detailed text commentary to understand key satisfaction drivers.
How we work
How we deliver sentiment analysis
Sentiment Taxonomy & Labeling Rules
Defining sentiment scoring scales (3-point, 5-point, continuous) and domain-specific sarcasm guidelines.
Annotated Dataset Development
Creating domain-specific training sets annotated with targeted aspect tags and sentiment polarity labels.
ABSA Transformer Model Training
Training BERT aspect-based sentiment models that connect specific entity targets with sentiment polarity.
Real-Time Alert Threshold Setup
Configuring automated email and Slack alerts when negative sentiment spikes occur for priority enterprise accounts.
Visual Dashboard Deployment
Building real-time sentiment trend dashboards displaying overall brand health scores and feature-level sentiment breakdowns.
Related capabilities
Related capabilities in Computer Vision & Language AI
Information Extraction
Automating key-value extraction, table parsing and relationship extraction from unstructured business documents.
Speech Recognition
Building automated speech-to-text (STT) engines and acoustic models for call center transcription and voice command systems.
Speech AI
Developing conversational voice agents, text-to-speech (TTS) synthesis and real-time interactive voice response (IVR) platforms.
Document Understanding
Combining computer vision, NLP and OCR to analyze, classify and extract structured intelligence from complex business documents.
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Where this applies
Healthcare & Life Sciences
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Manufacturing & Industrial
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Banking, Financial Services & Insurance
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E-Commerce
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Questions & answers
Questions about Sentiment Analysis
Cannot find what you need? Our team responds to technical and commercial questions within one business day.
Ask a questionAspect-Based Sentiment Analysis breaks down a text into specific topics or features, identifying positive sentiment for one feature while detecting negative sentiment for another in the same sentence.
Sentiment analysis is quoted as a fixed-fee development project or integrated into ongoing brand monitoring retainers.
We fine-tune transformer models on domain-specific datasets, significantly improving sarcasm detection and context awareness over generic rule-based tools.
Next step
Discuss sentiment analysis with Acmez
Share what you need to change, build, integrate or support. We will map the practical next step.