What is the Fundamental Purpose of Sentiment Analysis?

There are millions of tweets and Facebook shared posts every day. Billions of people are using social media and sharing their thoughts by day and night. This huge amount of data is not easy to analyze especially when it comes to knowing the opinion of people about something. To get a final result about its performance, what majority of the people thinks about it. Thanks to sentiment analysis which made it easier for us than ever before. This is the fundamental purpose of sentiment analysis to analyze the sentiments, opinions, attitudes, and emotions of the people.

But if you want to know how sentiment analysis becomes able to do it, you should know about the purpose of sentiment analysis. This article will aim to answer about the basics of sentiment analysis and natural language processing, fundamental purpose of sentiment analysis and its workings. Before you know about the purpose of sentiment analysis, it is necessary to understand NLP.

Natural Language Processing:

It is abbreviated as NLP. Natural language processing is the main branch of sentiment analysis. The purpose of sentiment analysis and NLP is the same in one aspect. NLP is the vast field that includes other tasks than sentiment analysis alone. It is a process that includes various studies like computer science, artificial intelligence, and linguistics. As mentioned above, there are millions of sharing of what people are thinking about entities. It is essential to make machines understand the natural language so that they would be able to perform functions like translations and answering the questions. The natural language process is used to check the spellings and keyword searches. You can use it to find the synonyms. Google Translate, Amazon Alexa, Apple Siri and many other applications are using NLP for machine learning processes.

Difference Between Sentiment Analysis And NLP:

As mentioned above, NLP is the major branch that involves techniques other than sentiment analysis; for example, syntactic analysis, semantic analysis, tokenization, dependency parsing and many more. The basic purpose is to make the machines understand text and do some meaningful pattern extraction. But the purpose of sentiment analysis is only to categorize the emotions and opinions of people about an entity. There are many ways to perform sentiment analysis. It has many types. We will discuss its details below. The thing to keep in mind here is that sentiment analysis is the sub branch of its parent field: the natural language processing.

What Is Sentiment Analysis Or Opinion Mining?

Sentiment analysis is also known as opinion mining. It is sometimes referred to as emotional artificial intelligence also. It is the sub branch of natural learning process used to examine the emotions of public about an entity. A system is made to collect and group the opinions of people about a certain thing. Sometimes, machines use an automated method to convert the sentiment into text. There are many areas where sentiment analysis proves to be useful. For example, it can determine the marketing trends, you can track and analyze ad campaigns, etc. The purpose of sentiment analysis is to take the opinions of the people about a specific model. For example, a portion of food was good because of its taste but the packaging was not enough clean and proper. So, people may give positive, negative and neutral opinions about it. SA will gather and group those opinions for the sake of betterment of businesses.

Types Of Sentiment Analysis:

According to a dissertation help firm, depending upon the sentiments of the costumers, SA can be of many types. You can categorize the sentiments as positive, negative, and neutral. Sometimes feeling are involved in sentiments. It will make another type like angry, sad, happy and others. You can also consider SA as recommended or not recommended. But the major purpose of sentiment analysis is to make polar analysis of the product. Let us discuss some prominent types of sentiment analysis.

Polar Sentiment Analysis:

Polar sentiments are very useful in running businesses. It is the best and easiest method to take feedback about progress of the firm. It is a discrete yet elaborative technique for determining the thoughts of users. Poles may be defined as outstanding, positive, neutral, negative, and terrible. In terms of stars, your outstanding can be considered as five stars and likewise terrible would be given one star.

Emotion Detection:

One of the purposes of sentiment analysis is to judge the emotions of people. It is a fantastic technique to texture the feelings of people. Machine learning is getting advanced in this field. Now with the blessing of SA, you can examine whether people are happy or frustrated about a specific thing. They are angry or sad. For this purpose, lists of words and emotions they transfer are used. These lists are known as lexicon. These are complex algorithms through which you can easily justify the progress of a product.

Pros and Cons Of Sentiment Analysis:

Sentiment analysis has its advantages and disadvantages. Both have their own value in analyzing the things for taking them along.

Benefits Of Sentiment Analysis:

Sentiment analysis helps you out to analyze the customers’ feedback in a quick and effective way. A person can’t read hundreds and thousands of feedbacks given by the customers. Sentiment analysis makes things easy. You can chunk down the feedbacks in segments. These ways, you can get the idea about customer’s view regarding your business. You can automate the process to drill down and focus on different segments.

Disadvantages Of Sentiment Analyses:

Although sentiment analysis is beneficial regarding customers’ feedback, still it has some inefficiencies. Sentiment analysis is not the complete replacement of feedbacks. There are certain points mentioned by the customers. Sentiment analysis cannot replace the necessity of a complete feedback where customer points out significant aspects. You need to focus on certain points. Sentiment analysis can then further help you to know which comments you should read.

Conclusion:

Sentiment analysis is a great way to have the idea about customers’ views for your business. You can bring significant changes and advantageous aspects into your business by knowing about customers’ experiences and demands.