What are the Main Goals of Sentiment Analysis?

Opinion mining helps businesses extract useful data from any form of text. You can take reviews, comments, or any piece of text and analyze it to find negative and positive emotions. Analyzing these emotions allows you to cater to client problems and strengthen your relationship with your client. Whether you run a massive organization or a small firm, sentiment analysis tools help you manage a crisis, improve brand image, and shape company sales.

The mechanism uses algorithms, NLP, and various libraries to achieve accurate results. However, before going into the depth of the process, we need to understand what is the goal of sentiment analysis. You can accomplish multiple tasks when you use opinion mining in the right way. There are so many high-value insights that you can derive from any dataset using opinion mining.

The following paragraphs will guide you on what is the goal of sentiment analysis. Moreover, we will explain its process and use in our life.

Defining the Concept of Sentiment Analysis

The advancement in technology has allowed us to analyze text like never before. We need powerful tools for our business ventures. Businesses need to decode the meaning of customers’ comments to understand what they are doing wrong and how they can improve. That is what text analysis mechanisms do. It helps you dig out negative and positive sentiments from a sentence. When we write comments or reviews, we feel various emotions and our sentences express those feelings. Using an analysis technique, computer systems can uncover the meaning behind words. It’s all carried out by NLP and AI.

These advanced technologies can assess text, images, and audio files. Sentiment analysis falls under the domain of data analytics and offers valuable information. Whether it’s social listening, customer experience analytics, or social monitoring, all these are possible using opinion mining. If your question is, what is the goal of sentiment analysis, the answer is that it allows us to understand people’s emotions and feelings in real-time. Without this mechanism, you can never realize your mistakes or your client’s mindset.

Learning the Main Goals of Sentiment Analysis?

You might think that sentiment analysis can only determine the negative or positive sentiment hidden behind a piece of text, but there is more. Opinion mining determines the emotional tone of words. From the attitude to the intensity of emotion, you can interpret a lot from just a few words.

Brand Monitoring: The most crucial task done with the help of opinion mining is brand monitoring. You can analyze text to see how individuals perceive your brand. From your new collection to products on sale, everything receives negative or positive comments. Analyzing these comments allows you to find the position of your brand. If there is a misconception or misunderstanding regarding your brand, you can solve it.

Revealing Trends: We see a shift in market trends. You can collect user reviews from various channels and analyze them to find people’s liking. Afterward, these results can help you make suitable changes in your work.

Training chatbots: Apart from humans, emotion analysis also helps you train machines. In other words, you can train chatbots according to the information you get from the analysis mechanism. Your chatbots will judge customer mood and respond accurately. However, it requires training which is possible through sentiment analysis.

Finding Emotional Triggers: Several emotion triggers define how we will react to a situation. These triggers can also push us into making decisions. Using opinion mining, companies can find such emotional triggers and use them to create a positive influence.

Finding Customer satisfaction: Another goal achieved through emotion analysis is finding customer satisfaction. An efficient analysis process helps you understand customer mood and whether they are content with your services.

How to Perform Analysis?

Performing opinion mining involves natural language processing. Without NLP, the process can never be possible. The reason is that NLP identifies words, converts them to tokens, and performs all the data processing. With tokens and processed data, the system analyzes each word to find whether it has positive or negative emotions. At times, sentences can be neutral as well. If emotions in a text are negative, they get a sentiment score below zero. For positive sentiments, the score is higher than zero. Sentiment scores are the most crucial part of the entire process. Based on the overall sentiment score, we interpret the positive or negative nature of the text.

Using NLP for Opinion Mining

By now, we have an exact idea of what is the goal of sentiment analysis. However, we should also know about other factors used in the process, like NLP. It decodes human language. Apart from understanding, it also manipulates pieces of text to make them understandable for our machines. Unlike humans, machines cannot understand emotional intensity or sarcasm. Thus, NLP makes the interpretation possible.

Positive and Negative Sentiments

Experiencing various emotions is only possible for humans. We feel multiple emotions, like sorrow, happiness, and even anger. These emotions are evident in the text we write but might not mean anything to a computer. Thus, opinion mining finds these hidden emotions in words and scores them. Sentiment score varies according to the type of emotion. A piece of text can have negative emotions, portrayed through words like hate, anger, or disgusting. On the other hand, positive sentiments are identified through words like happy or satisfied.

Neutral Sentiments

Like positive and negative emotions, your system can also detect neutral sentiments. However, the score for neutral words will be zero, unlike positive and negative words. It is difficult for a piece of text to be neutral, but it is not impossible. Thus we train our model in a way that helps it to identify any emotion.

Analysis Software and Models

When it comes to opinion mining, we can use various types of analysis mechanisms to find underlying emotions in speech or text. These include:

Intent Analysis: It allows us to understand the user intent behind a message.

Contextual Semantic Search: CSS helps companies understand the context of a message. You can segregate feedback and reviews based on whether they relate to new products, complaints about customer service, or any other issues.

Aspect-based Analysis: We divide a dataset and score each component based on how negative or positive it is.

Applying Opinion Mining to Fulfil your Companies Goals

There is no better way to understand your audience other than opinion mining. It analyzes the sentiments of every individual and finds whether they like or dislike something related to your company. Using this advanced system, you can achieve multiple goals simultaneously. For example, you can improve your sales, find the reason for client dissatisfaction, and much more. The best part, you don’t need to put in any extra effort throughout the process because the system uses AI and NLP. All that you need to do is provide a dataset and wait for an accurate analysis report.

If you want help in running company matters, you can get in touch with VizRefra. We provide effective sentiment analyst services for every big and small enterprise. So connect with us and get every relevant detail.