AI Text Detection

our showreel


Sentiment Analysis Using NLP

Fri Mar 20 2020  ·  

 ·  5 min read
providing what their consumers want by using sentiment analysis

In the light of Enhancing Customer Experience

graphic dialog because


A businessman only becomes a great businessman when he is providing the best to his team and his customers. Customer Satisfaction is usually the top-notch aim to be achieved by an organisation. To deliver the products and services suiting their needs and desires not only gives satisfaction but also strengthens the business. Therefore, it becomes evident for any business firm to work up to the expectations of their customer.

Want to know how Sentiment Analysis works?

Technology is upgrading itself every day and so does the requirement of it. Machine Learning has made things possible that if done manually, it will take months to be done and will be expensive too. 

Natural Language Processing (NLP)- a program developed in order to make the machine understand human language and respond to it simultaneously as well. NLP is a field where Computer science, Artificial Intelligence & linguistics merge and together produces algorithms that translates the human language into the machine language (binary). 


The work of NLP’S sentiment analysis service is to produce an average understanding of the sentiment analysis based on the data fed to it. Thousands of data files, reviews, reports, comments and reactions are fed to the machine where the NLP algorithms or software runs a sentiment check on it by understanding the context of the data rather than just focusing on the keywords. NLP has the ability to understand even the complex human emotions and uncover the real emotion behind the written context.  


The company’s huge amount of data considered as invaluable is able to produce intelligent insights that lead to great strategies and success in future. Most of the organisations use this technology for the same purpose. We have provided a small demo or you to understand how it works:


Let’s assume there is a Company XYZ  that sells handmade chocolates and on delivery asks for feedback in return from the customer. A feedback form is usually displayed on the application or is sent via email where they ask to rate their product quality, packaging and delivery experience. The customer in return rates the product and services related to the product. The company has a set bar where the rating is displayed and the customer is usually asked to rate between 1-10 where:

8-10= positive reaction

4-7= neutral 

1-3= negative reaction

common review by costumers

Along with the rating a description box is added in the end to collect the review in terms of the context. Based on the collected data fed to the machine, the machine in return analyzes the data and produces the average sentiment summarization on it which later helps the organisation.  

Need assistance in Sentiment Analysis Using NLP?

CreateBytes believes in taking communication beyond words. Our team is an expert in working with NLP algorithms that can easily structure, analyse and produce an effective outcome out of your unstructured data. Further, on the basis of the produced outcome, our team will assist you in building strategies to fulfil your customer expectation and make your organisation competitive in your industrial field.  


Continue Reading...

Tagged with :

Web & App Development
Software Development
Product Recommendation
Mobile App Development
User Experience


Which NLP is best for sentiment analysis?

Hybrid approach. Hybrid sentiment analysis models are the most modern, efficient, and widely-used approach for sentiment analysis.


What is sentiment analysis and how is NLP used within sentiment analysis?

Sentiment analysis is an analytical technique that uses statistics, natural language processing, and machine learning to determine the emotional meaning of communications. Companies use sentiment analysis to evaluate customer messages, call center interactions, online reviews, social media posts, and other content.


Which neural networks are best for sentiment analysis?

Convolutional neural networks is a model that performs particularly well on sentiment analysis tasks and is commonly used in computer vision models.


What are the types of sentiment analysis?

Modern-day sentiment analysis approaches are classified into three categories: 

  • Knowledge-based
  • Statistical, and 
  • Hybrid

Start a new project

Kindly fill up the below details and We will contact you ASAP!