With the rise of social media, it’s more important than ever to monitor how people feel about your brand. Negative comments, especially waves of negative comments, can make or break a reputation. But how do we monitor online comments or articles when they appear constantly? The answer to this question lies in sentiment analysis. Sentiment analysis is one of the most crucial metrics in social listening because it gives us invaluable information about the opinions and emotions of audiences about a brand.

What is sentiment analysis?

Sentiment analysis is the process of analysing emotions in text. That process is also called opinion mining, and it’s used to understand how people feel about specific topics based on their social media comments or articles online. Usually, sentiment can be negative, neutral, or positive. It can also detect more elaborate emotions such as anger, annoyance, sadness, happiness, etc.

How does sentiment analysis work?

Sentiment analysis works through elaborate algorithms based on Natural Language Processing (NLP) and machine learning. Thanks to these technologies, we can determine sentiment automatically and avoid human bias in the process. The sentiment is typically determined by scoring the text on a scale from Totally negative to Totally positive. That allows the machine learning algorithm to define whether a sentence has a strong negative language or just a milder but still negative language.

Several algorithms can be used in sentiment analysis, depending on the data type you want to analyse. The algorithms are rule-based, automatic, and hybrid.

  • Rule-based: based on manually crafted rules to automatically detect the polarity of sentiment.
  • Automatic: based on machine learning techniques.
  • Hybrid: they combine both manual and automatic techniques. A huge plus of the hybrid model is that it is more accurate.

Where can I use sentiment analysis?

You can apply sentiment analysis to various industries, from sales & marketing to PR or politics.

Reputation management

One of the most common uses for sentiment analysis is to manage brand reputation. Online audiences share their opinions by commenting on social media, sharing blog articles, or writing reviews. These opinions can serve as a source of information for PR and marketing teams.

That is why insights from social media comments can be helpful to detect any arising reputational problems and prevent them from developing full scale. In the case of negative sentiment, PR teams can use that data to address negative opinions or even prevent a reputational crisis.

Customer service

Customer services specialists can use sentiment analysis to monitor how people feel about a product or service. With sentiment analysis tools, you can scan for negative opinions or feedback. That allows you to use negative feedback to your advantage and improve your products.

Having a clear understanding of what your customers like and dislike will boost your customer service efforts. Last but not least, by using sentiment analysis you can monitor for negative opinions and react quickly.


Sentiment analysis can be used in political science as well. For example, a 2018 study used sentiment analysis to determine political homophily during the 2016 Presidential elections. The results from the research showed that most of the negative comments came from Trump supporters, while Hillary supporters had homophily in various scenarios.

You can also apply sentiment analysis to political PR. Political PR experts can use sentiment analysis to determine how the public receives a political campaign.
Sentiment analysis is often used by academic research too. There are many papers dedicated to analysing political communication using sentiment analysis. Results from these studies can show us the level of political polarisation or understanding of political messages.

Market research

Sentiment analysis is a powerful tool for market research. It provides reliable information based on large amounts of data while saving time and money from classic market research approaches. With sentiment analysis, marketers can use real-time data on the audience’s opinions and attitudes towards a brand.

Not only that, but it also gives marketers an idea of why the audience feels that way.

Marketers also use sentiment analysis to monitor how audiences feel about their competitors. That can give marketing managers valuable insights into the differences between brands in products, customer service, and audience expectations. These insights can turn into an advantage when planning marketing strategies.

Are there any disadvantages to sentiment analysis?

Human language is complex, and it can be very subjective. Oftentimes, machines struggle with subjectivity. Take, for example, this sentence: ‘That clothing brand is fantastic, but their prices are ridiculous’. Here, the first half of the sentence is very positive, but the second part – is not.

Sometimes, context can be confusing, too. In some cases, words can have both positive and negative connotations, depending on the context.

Another thing that can be challenging for machines is irony and sarcasm. Sometimes it is hard for humans to recognise sarcasm in text, so imagine how hard it could be for a computer. For example, people may use positive words to describe unpleasant events or opinions.

That is why the best approach to sentiment analysis is to combine the algorithms with human knowledge.

How to choose a sentiment analysis approach?

There are many options for sentiment analysis tools online. You can decide to use the online tools or build sentiment analysis software. Both methods have their advantages and disadvantages.

Building your sentiment analysis software is a great way to customise it to your exact business needs. However, developing your software will take a significant amount of time and effort. It usually takes around six months and a team of software engineers to finish a sentiment analysis software. That will lead to an increase in costs and efforts to monitor and update the software.

You can also use an online ready-to-use sentiment analysis tool. They are beneficial because you can use them straight away, and you don’t need to have any coding skills to build your own. Most online tools are simple to use and provide you with easy-to-access data and insights. That will ensure lower costs while providing you with the metrics you require.

Sentiment analysis results

We mentioned the industries or areas you can use sentiment analysis. But let’s talk about what sentiment analysis can do to improve your business.

Identify emerging trends

Trends come and go, that’s why it’s best to identify how your audience reacts to any emerging trends before you decide to use them. Sentiment analysis will help you understand how your audience feels about current social media trends.

That will help you decide if you want to use those trends in the first place.
For example, for some months, social media users paid attention to red flags in relationships. That theme quickly turned into memes and comedy posts, where people exaggerated what they feel is a red flag in dating. Some brands paid attention to that and used it to create funny content. The make-up brand “Nyx”, for example, posted a meme on Instagram with a quote saying: ‘I don’t like girls who wear make-up’ followed by several red flag emojis.

Get feedback on your products/services

Customer feedback was always a significant factor for companies developing or launching new products/services. And social media is a great place to get honest customer feedback about your products or services without relying on customer surveys.

People love posting or commenting about their opinions on almost anything – from products to movies and politics. This is information you don’t want to miss out on. You can use online opinions to your advantage even before launching a new product to see whether the audience is interested in such products. Or you can use sentiment analysis to monitor how your audience feels about your products to improve them.

Identify potential problems

Social media users don’t shy away from sharing negative opinions or experiences with a brand. While this can potentially be problematic for brands, it is also a great way to spot and tackle issues right away. To do this, brands often rely on sentiment analysis.

By using this tool, marketing and PR teams can notice negative opinions quickly and take the matter into their own hands before it becomes a scandal.

Monitor competitors

Monitoring competitors is something every brand should do. After all, social media users share their opinions about everything. You can use that information to understand better what they like and dislike about brands in the same category as yours.

Key Takeaways

  • Sentiment analysis is a great way for brands to understand their audience’s opinions.
  • Sentiment analysis is based on Natural Language Processing (NLP) and machine learning and usually divides the text into positive, negative, and neutral.
  • Brands can use sentiment analysis in many industries, such as market research, politics, customer service, or reputation management.
  • Sentiment analysis is not perfect. Human language is complex, and machines can be confused by sarcasm, irony, or subjectivity.
  • Sentiment analysis can be done by building your software, or by using online tools.
  • Sentiment analysis can aid your business goals like identifying trends, receiving feedback on products/services, identifying potential problems, monitoring competitors, and many others.

At A Data Pro, we know how crucial audience insights are, which is why we developed multiple tools and services that can help you understand your customers better. Our team of multilingual experts work with the most up-to-date technologies to help you extract the information you need, so you can focus on perfecting your marketing strategies. You can explore our services here or contact us with any specific questions or requests.