Types of Sentiment Analysis

Types of Sentiment Analysis Repustate's all-in-one sentiment analysis platform

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What are the types of sentiment analysis methodologies?

There are three types of sentiment analysis approaches that a business can employ - document-level, topic-level, and aspect-based sentiment analysis.

These approaches can be applied depending on the size and complexity of the text data. Let’s explore them in detail.

1. Document-level sentiment analysis 2. Topic-based sentiment analysis 3. Aspect-based sentiment analysis

1. Document-level sentiment analysis Document-level sentiment analysis aims to classify the sentiment or emotion based on the information in a document. In basic text analytics, semantics in a document can be drawn from three areas - word representation, sentence structure and composition, and the document composition itself.

It is simple as long as there is only one sentiment in the complete text. However, this approach is not very helpful if the sentence composition and word representations are complicated. In such cases, the nuances of the comment can be lost, and the results will be inaccurate.

2. Topic-based sentiment analysis Topic-based sentiment analysis finds the sentiment related to a specific topic. This model identifies and extracts topics in the data through keywords and aggregate scoring. It also takes into account the mood reflected on the topic.

A machine learning model can be trained for each of these topics and customized as per the business or industry requirement.

For example, topics within healthcare can be the ER, prescription dosage, patient wait-time, etc., while in hospitality, it can be food, reservations, or service.

3. Aspect-based sentiment analysis Aspect-based sentiment analysis (ABSA) system identifies the main aspects or features of an entity and provides an estimate of the average sentiment expressed for each aspect.

For example, an entity could be a luxury watch and the aspects/features could be its battery life, design, colours, and such. In other words, aspect-based sentiment analysis is a more granular approach to analysing reviews.

Comparison of types of sentiment analysis using restaurant reviews.

Example of sentiment analysis in healthcare reviews

Which is the best way to do sentiment analysis?

The best approach is always the one that provides the most significant degree of granular results and delivers tangible insights that can be used to make a real difference to your business.

Ultimately, aspect-based sentiment analysis is going to provide you the best results if your product or service attracts customers who tend to write long, complex, and detailed reviews but it tends to be most time-consuming.

This is mostly the case in technology reviews or luxury item reviews like watches and electronic gadgets. The most important poit is that you begin to apply sentiment analysis to your text data if you have not already. That is the first best step.

What makes Repustate’s sentiment analysis tool stand out?

Repustate’s sentiment analysis solution processes thousands of reviews per day for hundreds of clients, worldwide. It enables real-time social media sentiment analysis and even saves unforeseen PR crises. More importantly: 1.

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Our AI-powered software provides both topic-driven and aspect-based sentiment analysis for the most accurate results in 23 languages and dialects.

Its processing speed is 1,000 reviews per second.

Our solution is highly customizable and scalable because we know that each business is unique, even if in the same industry.

Understand your data, customers, & employees with 12X the speed and accuracy.

Thank you!

Visit: www.repustate.com to learn more