Machine Learning Based Real-Time Sentiment Analysis

Business Impact

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Customer sentiment analysis is crucial for business growth as it helps in determining customer experience and identifying customer needs.

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Facial recognition and monitoring reviews of customers are common ways to determine customer attitudes about a product/service.

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To get accurate results, OptiSol developed a text analytics model that collects tweets added by customers about products and performs sentiment analysis to classify customers’ emotions.

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Every tweet contains an explicit and implicit emotion, and current AI models can vastly classify them into Positive, Negative, or Neutral based on the core sentiment.

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But to further understand the personality of a person deeply, our AI model works real-time providing more defined sentiments like Happiness, Sadness, Anger, Hate, Confused, etc.

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Technology Stack

Solution Overview

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The contents of the tweet are pre-processed, and irrelevant data are dropped.

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The tweets along with their respective sentiment labels are split into Train and Test set are then passed into 3 models, namely Universal Sentence Encoder (USE), LSTM and doc2vec model.

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The performance analysis is done on the models, and it is concluded that the USE model works the best among the available options.

Trusted and Proven Engagement Model

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

Awarded Bronze Trophy at CII National competition on Digitization, Robotics & Automation (DRA) – Industry 4.0

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50+

AI & ML
Engineers

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40+

AI & ML
Projects for
reputed Clients

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5 yrs

in AI & ML
Engineering

Awarded as Winner among 1000 contestants at TechSHack Hackathon

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