How to Do Sentiment Analysis

You need to understand your audience when building a brand. How customers feel about your brand or business is crucial to its success. If you understand the nuances of their feelings you’ll get a step ahead of your competitors.

It isn’t just about the general phrase “they love my product” or “they don’t love it.” It stretches to minor details that help make up your services or products and how you present them to your customers.

If several things rub your consumers the wrong way, you need to keep on top of them for your business to thrive. What consumers want isn’t always consistent and obvious. It isn’t guaranteed that if a product performs well at a given time and place, it’ll flourish in another. What can you do to keep on top of customer perception and your feedback on it?

In this internet era, website reviews and social media posts are published every few seconds, meaning there is much information to analyse. That is where sentiment analysis becomes useful. This guide will help you understand sentiment analysis and how to do it. Let’s dig deep to unearth more!

What is Sentiment Analysis?

Sentiment analysis includes detecting negative and positive sentiments in a block of text. It’s, in most cases, used by businesses and brands to detect sentiment in social media posts and website reviews. They also use sentiment analysis to understand customers and gauge brand reputation. Sentiment analysis primarily focuses on a text’s polarity (neutral, negative, or positive).

It stretches beyond polarity to help businesses and brands detect specific emotions and feelings (sad, happy, angry, etc.), urgency (not urgent or urgent), and intentions (not interested or interested). The most popular sentiment analysis types include the following:

  • Graded sentiment analysis
  • Emotion detection
  • Multilingual sentiment analysis
  • Aspect-based sentiment analysis

How to Do Sentiment Analysis

You can do sentiment analysis in four simple steps, which include the following:

  • Data Collection: Collect high-quality data from your customers. You can obtain this kind of information from platforms such as Twitter, Facebook, and Amazon reviews. Once you collect your data, upload it to the sentiment analysis API.
  • Data Processing and Analysis: Your data needs to be analysed and processed. Data processing varies depending on the medium type, such as video, audio, text or images. The analysis process includes tags, topic classification, training the model and analysing for sentiment.
  • Data Visualisation: After analysing the data, it’s converted into charts and graphs. Data visualisation allows you to easily interpret the processed information and identify the main areas of focus.

Sentiment analysis offers several benefits, which are: it eliminates human bias, helps process huge amounts of data and allows you to get real-time analysis and insight about your company.

Whether it is brand, product, service or labour markets analysis, you need to partner with a top-rated sentiment analysis solution to obtain correct outcomes and remain competitive in your industry.