Sentiment Analysis Services for NLP Projects

Analyze customer sentiment or social media trends through our sentiment analysis services to identify positive sentiment or negative sentiment in data.

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We Scale Teams for:

ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX

Sentiment Analysis Services at Label Your Data

The sentiment analysis process is a comprehensive service that our team provides for our clients working on developing an NLP algorithm capable of estimating the mood of a person. Our annotators analyze textual data or listen to audio recordings to assess the emotional tone of the data.

Customer Sentiment Analysis
Social Media Monitoring
Market Research & Competitive Analysis
Customer Sentiment Analysis

Customer Sentiment Analysis

Our annotators carefully assess customer reviews, enabling efficient use of NLP in customer support or any type of interaction with the user to enhance customer satisfaction and improve products or services.

Social Media Monitoring

Social Media Monitoring

By analyzing user comments and social media feedback, our annotators can detect sentiment to enable NLP systems to understand public perception of a brand. This enables proactive measures to enhance its reputation.

Market Research & Competitive Analysis

Market Research & Competitive Analysis

Our sentiment analysis experts analyze people’s moods expressed in social media posts, surveys, and online discussions, allowing our clients to gain valuable insights into consumer preferences, trends, and competitors’ performance.

Exclusive Benefits of Our Sentiment Analysis Services

We provide a secure, high-quality sentiment analysis service for your NLP algorithms that provide insights on customer sentiment, brand reputation, social media trends, and data-driven decisions.

Multilingual Service

Multilingual Service

We can perform sentiment analysis in 55 different languages. This allows for comprehensive sentiment analysis of your text data for valuable insights and well-informed decisions across diverse linguistic contexts.

Diverse Team

Diverse Team

Our diverse team represents various ethnicities, geographical regions, and cultural backgrounds. This way, we ensure unbiased sentiment analysis by understanding different emotional levels across nations.

Flexible QA

Flexible QA

For sentiment analysis, we recommend a cross-reference QA, where at least two annotators work on the same dataset. We measure their agreement rate and evaluate disagreements separately, ensuring high-quality results.

How We Perform Sentiment Analysis

Our experts ensure that you receive the best quality annotations to develop NLP algorithms that offer valuable insights, address customer needs, and make informed business decisions.

Data collection

Data collection

Data collection usually happens on the client’s side. But if you don’t supply any data, our team performs data collection at your request.

Project & team requirements

Project & team requirements

At this stage, we coordinate with you the key project details to solve a particular sentiment analysis problem. Together, we decide on the process, labeling criteria, and sentiment analysis tools. We also discuss if a specific background is necessary, and if so, we proceed with hiring the right people for the project.

Pilot

Pilot

As we receive the first batch of text or audio data, our annotators run a small annotation sample to verify all the edge cases with you. A free pilot helps you decide whether our sentiment analysis service can meet your demands.

Full-scale sentiment analysis

Full-scale sentiment analysis

Once the pilot is done and the results are satisfactory, we proceed to full-scale annotation. On request, we can set up on-site teams and provide the option of working in the office. We perform sentiment analysis in batches, allowing you to track progress.

Quality assurance

Quality assurance

Before sending the completed annotations, we ensure their quality and validity by performing a thorough QA. For this task, we strongly advise using cross-reference QA with multiple annotators to ensure accuracy and impartiality.

Why Choose Label Your Data?

Our 10+ years of experience in building remote teams allows us to expertly navigate 500+ data annotators and provide high-quality sentiment analysis services in 55 languages. Choose us as your sentiment analysis services provider for quality, speed, and security of your data.

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FAQs

Which companies use sentiment analysis?

Various industries, including retail, finance, social media, and customer service, rely on sentiment analysis service companies to gain valuable insights from customer feedback and enhance decision-making processes.

Is sentiment analysis AI or ML?

Sentiment analysis involves the application of both AI and ML to analyze and interpret the sentiment expressed in text data. However, sentiment analysis as a service or an AI-powered sentiment analysis system combine the capabilities of both, enabling businesses to leverage advanced technology for this task.

What does the sentiment analysis process look like at Label Your Data?

Similar to a sentiment analysis company, our annotators perform data collection, text preprocessing, feature extraction, multi-class sentiment classification, and result interpretation. We use NLP techniques to analyze textual data and determine the emotional tone expressed within the text.