What is Sentiment Analysis and how does it work?

Sentiment Analysis is a process for quantifying and scoring language, driven by artificial intelligence and machine learning, used to identify the contextual sentiment of written language. Thanks to specific scoring mechanisms, it helps us monitor emotions within texts, and evaluate their character. Individual sections are then assessed with a sentiment score, determining the writer’s attitude and the overall mood of the text.

In order to find these opinions, Sentiment Analysis leverages a method called Natural Language Processing (NLP)—a system built to extract specific expressions and statements from text and tell the difference between all the words. The process of determining the emotional tone behind a series of words as positive, neutral, or negative is based on sentiment algorithms, that can detect expressions like:

• Simple statements: recognizing a positive word in “We enjoyed the stay”
• Negation: noting the difference between “The product is great” and “The product is not great”
• Modifiers: paying attention to the emphasis in “I really love this brand”

Thanks to NLP’s ability to break down language into shorter, elemental pieces, we can analyze the sentiment on a granular level. That means that the algorithms get to zoom in closely, as to evaluate individual words within larger fields of texts, understand relationships between the pieces, and explore how the pieces work together to create meaning. That way, attributing sentiment labels is done with an increased level of accuracy, providing us with more reliable results

Opinion Mining to enhance your social listening experience

First and foremost, Sentiment Analysis, in this case also referred to as Opinion Mining, is extremely useful for social monitoring. By mining opinions expressed through written online communication, such as comments on social media, reactions underneath a blog post, customer reviews, or written survey responses, you can gauge how customers and employees feel about your brand or specific topics. The collected data can then be leveraged to build a stronger, more effective online strategy.

Continuous monitoring of attitudes and opinions also helps brands identify pain points and areas for improvement in the product, offered services, or even the effectiveness of delivered customer support. In case of a crisis, it plays a crucial role as it supports reacting in a timely manner and responding appropriately, increasing your chances of resolving the problem before it gets out of control.  

At the same time, measuring social sentiment gives us a helping hand when it comes to better understanding our audience and their specific needs. Knowing who we’re speaking to, what is the motivation behind their purchasing decisions, and what kind of content is valuable for them enables us to offer a more personalized user experience and improve visitor engagement.

Induce positive sentiment through your digital content

Another—no less significant—way to leverage Sentiment Analysis is in the process of content creation. It’s a very handy tool as it evaluates the overall mood of your text, as well as gets a sense of the impression in its individual segments. By understanding what sort of emotions can be invoked by future readers before the texts get published, content editors, copywriters, or content managers can foresee and prevent any possible misunderstandings.

By finetuning the tone and the writing style to depict positive sentiment, you’ll be able to craft much stronger content, and send the right message that will resonate better with your audience. It will boost your brand’s marketing efforts, such as brand awareness, lead generation, thought leadership, customer acquisition, and customer loyalty, as these are directly influenced by how audiences feel about your company and its co

Analyze the sentiment of your content directly in Kentico Xperience

To save both marketers and developers significant amounts of time and the hassle of running the Sentiment Analysis through a third-party tool, this future-proof functionality can now be leveraged directly within the Kentico Xperience digital experience platform. Since launching Kentico Xperience 13 Refresh 2, we have boosted the DXP with features to suit both use cases described above:

Content creation:

Content editors can now run the analysis in any given text field (e.g., text areas, rich text editor, etc.) during the process of creating content. Every entity and its individual sentences, as well as the document as a whole, is assigned a sentiment score, depicted by a color-scale. To better understand the evaluation, it also includes an easy-to-digest explanation with the reasons behind individual results. This way, you can be aware of the mood your text induces and steer it towards the desired impression as you go.

User input:

It is now possible to leverage the Sentiment Analysis in any custom field or widget within Kentico Xperience, thanks to the pre-prepared API layer, supporting the access to Azure Cognitive Services' Text Analysis API directly in the product. At the same time, it oversees the html as well as the 5120-character limit, set by Azure, internally.

On top of it, marketing automation flows can be prepared to automatically follow up on chosen results, which presents a fantastic, automated way to quickly detect negative or sensitive user-generated inputs and react promptly. This feature’s practical highlight is a lifeboat for companies that don’t want to lose any precious time on saving a situation that could otherwise negatively impact their business.