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Predictions: How does AI get the Sentiments?

Artificial Intelligence is a part of the modern world, and it has even made a special place in marketing, customer care, and more. But when it comes to handling customers or target groups, the sentiments of people are involved. So how does AI get the sentiments?

To understand that, let’s take a look at Sentiment Analysis and AI applications in it.

What is Sentiment Analysis?

Sentiment Analysis is a complex method of analyzing consumer comments and feedback. It is a tool for identifying their thoughts. This process helps to understand how customers feel about the company’s products/services. For that, the words, sentences, and even sentence fragments are examined.

Doing so helps to pick up on the tone of a statement, question, or exclamation. Often, consumers mask negative comments with sarcasm. These cannot be detected if their words are not analyzed properly. Obviously, AI needs to be intelligent to catch the tone and identify negative or positive connotations.   

Importance of Sentiment Analysis    

Sentiment Analysis is an excellent tool for companies to understand the opinions of the customers. After all, customers’ thoughts are critical for companies. It helps improve their products and services, communication, and customer engagement. It also helps identify the influencers. 

Sentiment Analysis has many possibilities, especially the information that AI can generate from unstructured data. Affective computing of feelings, moods, and attitudes can be a valuable tool in predictive analytics. It can help predict the response of the audience and also manage employee engagement.

With the help of Sentiment Analysis, AI can now take note of every comment under every survey, thus making the best use of feedback. They no longer have to be left for someone from the customer service to read at their prerogative. Sentiment Analysis has also attained a 90% accuracy rate.

It is evident that the technology has already reached its maturity stage. It can review both textual feedback and customer calls to detect signals and cues. These help develop behavioral guidance. It is known that empathy and emotional intelligence are of great importance in improving communications.

Sentiment Analysis plays an essential role in this. Thus, it has taken over the world. Sentiment analytics is no more a concept that will materialize in the distant future. The world is already using advanced AI technologies to analyze sentiments. From banking and stockbroking to e-commerce sites – AI is everywhere.

How Sentiment Analysis and AI Work

Sentiment Analysis uses two AI sub-fields, NLP (Natural Language Processing) and MI (Machine Learning). Let’s find out how each of them works:

a) Natural Language Processing

NLP is responsible for transforming human language into a language that machines understand. Using syntactic techniques, it analyzes the structure of a given text. Then, using semantic techniques, it figures out the meaning of the text.

POS tagging, lemmatization, tokenization, etc., are techniques used for this purpose. After processing the text using these techniques, Machine Learning algorithms come into the scene for the purpose of classification.   

b) Machine Learning

ML makes predictions on the basis of the patterns that it recognizes in data. In order to do that, it does not need specific instructions. ML algorithms are intelligent enough to learn from examples or training data fed to them.

The training data must include examples of different emotions reflecting in text form. These will help it classify text by sentiments. Eventually, the model will learn to associate new text with a specific sentiment tag.  

Applications of Ai-Enabled Sentiment Analysis

AI-enabled Sentiment Analysis has started to become an essential tool for companies. It helps get an insight into customers’ minds. It also comes in handy for understanding the thoughts and emotions of employees. But it is mainly used to understand customer feedback, the urgency of a support ticket, mentions on social media, etc.

With the help of Sentiment Analysis and Artificial Intelligence, you can improve in different areas like –

  • Customer care
  • Social media
  • Market research
  • Brand monitoring
  • Employee feedback

It can be said that in the not-so-distant future, Sentiment Analysis will be used to dig deeper into human emotions. It will help machines understand the sentiments expressed through interactions, comments, and feedback even further. This will help companies personalize their responses even further.

Final Words:

From politics to PR and marketing – every field can benefit from AI-based Sentiment Analysis. But to make the best use of Sentiment Analysis, companies must invest in finding team members trained in it. That’s because Sentiment Analysis involves complex algorithms and processes.

One thing is for sure: Sentiment Analysis with AI will open many career opportunities. To make yourself eligible for them, fine-tune your Machine Learning knowledge – with our <Business Analytics and AI> course. Register today! 

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No. 7 In Part-Time MBA Programs
By submitting the form, you agree to our Terms and Conditions and our Privacy Policy.
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