What is Sentiment in Sentiment Analysis?

Sentiment in Sentiment Analysis – A business’s success is determined by how its customers feel about its products and services. Positive feedback means that your efforts are moving in the right direction. A survey recently stated that good experiences could help raise a business’s revenue by around 4-8% more than their competitors. But how can a business analyze what is the emotion hidden in the words of the consumer?

With the development of great e-commerce and SaaS tools, businesses are now introducing Sentiment Analysis into their organization. It is a popular tool that can benefit the business in plenty ways. Let’s take the example of Twitter. Daily, millions of people share their opinions about a product or service on it. By using sentiment analysis tools, a business will get different insights on how exactly people feel about a product.

But what exactly is this tool? How can your business benefit from it? Are there any challenges or features of that businesses should be aware of?

To get answers to all these questions, keep reading on:

What is Sentiment Analysis? 

Also known as opinion mining, Sentiment Analysis is a popular NLP (Natural Language Processing) solution. It helps recognize the emotions and feelings behind the customers’ words. From a business perspective, Sentiment Analysis is used to determine the customer’s emotions and their approaches toward a product, service, or brand.

Usually, emotions are divided into three categories: positive, neutral, or negative. These categories might sound quite simple to identify. But in the world of words, it is difficult to determine the true meaning of what the customer is trying to say.

Before diving into knowing more about Sentiment Analysis, let’s understand what is Sentiment?

What is Sentiment?  

Sentiment refers to a person’s opinions, emotions, and attitudes. They are impressions the customer builds for a product or service on a subjective basis. As mentioned above, they are basically of three types: neutral, negative or positive sentiment. But along with these, more intense emotions like sadness, happiness, anger, and frustration are also included.

The variety of emotions and the numerous ways to express them make it difficult to understand what is going on in the head of the customer. With the help of Sentiment Analysis, it gets a bit easier to figure out what your consumers are trying to say.

Main Types of Sentiment Analysis 

Sentiment Analysis can be put into three categories:

  • Fine-Grained Analysis
  • Emotion Detection
  • Aspect–Based Analysis

To understand them more elaborately, keep reading:

Fine-Grained Analysis: 

The basis of fine-grained analysis comes from the polarity of one’s perception and opinion. It means one can either have a simple positive sentiment or negative sentiment towards a particular product or service. While analyzing a few simple texts like news articles, tweets, and product reviews, people usually have a straight forward outlook. Either they will love it or hate it.

There are chances that one can have somewhat complicated variations of the emotions, like neutral sentiment. Using complex fine-grain analysis you can easily understand the complexity of texts and figure out its approaches.

For Example: “My mobile stopped working after five weeks of use” this online review helps a business understand what is the take of customers on their product. In case of any defaults, businesses can improve them according to the reviews they receive.

Aspect–Based Analysis: 

Aspect–Based Analysis deals with categorizing the data by aspect. It identifies the emotion behind customer feedback by associating them  feelings that a person may have for an aspect.

Let’s understand it by breaking it into two terms:

Aspects: The topic or feature that is being talked about.

Sentiments: opinions about a particular aspect.

By introducing aspect-based analysis, a business can clearly understand what customer feedback has to say.

For Example: “The food was delicious, but the staff was not cooperative” With this statement, one can see that there are two types of emotions that are portrayed in one sentence. Initially, the aspect is food, and the emotion behind it is positive. However, in the second half, the aspect changes for the staff, and the feeling goes all negative.

Emotion Detection 

Ever been confused about what the customer has to say in the text? Is he being angry, happy, or fearful? With the help of emotion detection analysis feature, you can determine the customer’s experience towards your product or service. It will help you in building up a product or service by eliminating all its drawbacks.

For Example: “I loved the creamy sauce but the pasta was little undercooked.” You can easily figure out the dissatisfaction of the customer from these lines. Emotion Detection Analysis will provide you with more insights on that.

After understanding all about the major types, the next question is about its usage:

What can you use sentiment analysis for? 

It is key in helping a business understand customers’ needs. Here are a few major benefits of this modern-day tool:

Building Brand Reputation: 

The internet is the biggest place where all your customers will always be available. More specifically, the social media platforms: Facebook, Twitter, LinkedIn, Instagram, etc., where businesses can interact one-on-one with their customers.

With the assistance of this tool, you can monitor all your activities on these platforms and get reviews on how your campaigns are working. Thus, helping in building a good brand reputation.

Marketing Research: 

Be it looking out for any new trend or analyzing the entire market, you would require analyze the sentiments of the customer to get quality information. For example, what does your customer expect from you? What are their likes and dislikes? All information can be gathered through this versatile NLP tool.

Customer Service: 

In the customer service industry, this tool plays a vital role in understanding the tonality of incoming calls. They can easily sort out the calls into two categories “urgent” or “not urgent.” After that, it’s up to the customer service agent on how they approaches the issues.


Like any other tool, you will always encounter issues and some challenges with this tool:

Difficulty in Interpreting: 

If not spoken verbally, it is difficult to understand what emotions your customers’ words portray. It can get even more difficult when someone has to analyze the content in a massive volume, especially if you are a well-renowned brand with millions of followers worldwide.

Funny Texts: 

You might have seen people often using sarcasm and irony to express themselves. But Sentiment Analysis sometimes fails to figure out the true essence of the text. As a result, it can often misunderstand the true essence of the message.

Visual or Audio Data: 

Videos and audios are not like texts. Their true meaning can be taken out of context easily by this tool. In the future, there are chances that the negative feedback can be put into the positive bucket by this tool.

Is sentiment analysis tool even worth going for? Conclusion: 

There are countless aspects of business where this tool can be used for like product analytics, brand monitoring, customer service, marketing research, analyzing reviews etc. With its incorporation in the existing systems, organizations can work more accurately and faster.

Now, you must be looking for a great Sentiment Analysis tool for your business, then VizRefra is your place to be! Backed up by an expert group of members, VizRefra will provide you with a perfect solution to help your business succeed.