Whether for the purposes of researching the market or checking employee satisfaction, you have probably at least once seen, if not even created, a questionnaire. We can’t deny that these have always been an effective technique for gathering some statistical data and helping people come to certain conclusions. Their effectiveness doesn’t subdue and it appears that these can do much more than you actually thought.

Have you heard about sentiment analysis yet? This particular technique can help you guess the emotions behind people’s answers and I am sure that we would all love to be able to do that. Yet, this is a fairly difficult task and, as you can see here, there are those less challenging cases and then there are more challenging ones that can put the algorithms to hard work before the score is announced.

Before we get to the actual score, let us first make it perfectly clear what sentiment analysis is and how it actually works. The fact that I said it can guess the emotions behind people’s answers might make it all seem like magic, while the truth is that it is actually pure science. So, if you thought that this had anything to do with magic, let me assure you that it doesn’t. Of course, there’s no better way to assure you than by giving you clear and direct explanations.

What Is Sentiment Analysis?

This practice is also called opinion mining and it, basically, uses machine learning, natural language processing and text analysis in order to both interpret and classify people’s emotions in subjective answers. It is rather important for every single business out there because it allows them to gauge brand reputation, detect sentiment in social data, as well as better understand their customers. And, if that doesn’t lead to success, then I don’t know what does.

To put things even more simple, sentiment analysis is actually a text analysis technique that can determine whether a particular opinion in a certain text is positive or negative. The text can be a simple clause, a sentence, a paragraph or a whole document. The process will be successful regardless of the type of the actual text.

By determining the emotional tone behind certain words, you can determine the attitude and the opinion that is contained in a specific text, whether it is an online mention or a direct answer to your survey. The ultimate purpose of these algorithms is to go as far as detecting whether a particular statement is positive, negative, or neutral. That simple piece of information certainly comes in handy and can even lead to some changes in the way you do your business.

Read more about opinion mining here.

Where Is It Used & Why?

You are now probably wondering where this specific type of analysis is actually used, so let me give you a clear and straightforward answer. While the technique can be used in order to discover and collect people’s opinions about certain products, services, as well as brands, the truth is that sentiment analysis is nowadays mostly used on social networks. The practice is being accepted and adopted by organizations and businesses all across the world, simply because it allows them to collect and analyze useful data that can help them be more successful at what they do.

If I were asked to pinpoint the industry in which sentiment analysis is mostly used, I wouldn’t be able to do that easily, since it spreads across a large number of areas. Even politics are strongly influenced by this particular research technique, but I suppose that doesn’t come as a surprise. After all, politicians are all about impacting the public opinion and they can’t do that before first determining the current opinion.

Now that you understand where this technique is used, you will certainly be curious as to why. That has always been the most important question and although it might all seem like a mystery, the answer to the question of why is definitely rather simple. Sentiment analysis allows you to gain insight into public opinion and emotional reactions regarding certain documents, interactions and events.

Let’s explain the importance of this by using businesses as an example. If you own a company and you are trying to sell a product or a service, the opinion of your customers and prospects will always be a huge determinant of your success. This means that you want to know what those people are thinking in order to better understand what it is they actually need and want, so that you can then tailor your products and services to meet those requirements.

When you receive your sentiment analysis score, you will be able to understand what your strong points are, as well as which particular aspects could be improved. For example, you might find that people love the service you are providing or the product you are selling but they, for instance, hate your customer service or your pricing plans. That immediately gives you an idea about which particular aspects you should focus on improving.

What Is A Good Score?

If you have decided to use this specific technique and now you want to learn more about it, the first thing you will be curious about is, undoubtedly, the actual score. How can you know if your particular score is good enough and how can you decide that it isn’t great and that you should work towards improving it? Well, as it usually goes when it comes to businesses, there is certainly not a straightforward answer to this question, since it all depends on your individual parameters and scoring models.

Here is the most precise thing I can tell you. When you start using this technique, you should set a minimum score for both positive and negative thresholds. That way, you will have the perfect scoring system designed to work for your individual cases and that will certainly help you determine whether your final score is good or whether it should be improved.