Sentiment analysis

Text Analytics

Our Sentiment Analysis engine is a real-time text analytics platform that processes customer feedback, reviews, social media comments, and other text data to identify emotions, tone, and opinions. Using advanced LLM technology and zero-shot classification, the system can analyze sentiment across multiple dimensions including polarity, emotion, and intent. The engine processes text in real-time, providing instant insights that help organizations understand customer sentiment, track brand perception, and respond proactively to feedback and concerns.

Completed20244 months

Project Overview

Client:Social Media Analytics Inc
Duration:4 months
Team Size:5 developers
Status:Completed

Technologies Used

sentiment analysisemotion detectionzero-shot classificationLLMs

Key Features

  • Real-time sentiment processing
  • Multi-dimensional emotion detection
  • Zero-shot classification capability
  • Batch and streaming analysis
  • Sentiment trend tracking
  • Custom sentiment model training

Challenges Overcome

  • Handling sarcasm and irony
  • Context-dependent sentiment analysis
  • Processing multilingual content
  • Dealing with ambiguous expressions

Results Achieved

  • 95% sentiment classification accuracy
  • Real-time processing of 10K+ texts/second
  • 80% improvement in response time to negative feedback
  • 70% increase in customer satisfaction tracking