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. Types of
Sentiment Analysis
Repustate's all-in-one sentiment analysis
platform
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2. 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

3. 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.

4. 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.

5. 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.

6. Comparison of types of sentiment analysis
using restaurant reviews.

7. Example of sentiment analysis in healthcare
reviews

8. 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.

9. 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. Our AI-powered software provides both topic-driven
and aspect-based sentiment analysis for the most
accurate results in 23 languages and dialects.
2. Its processing speed is 1,000 reviews per second.
3. Our solution is highly customizable and scalable
because we know that each business is unique, even
if in the same industry.

10. Thank you!
Understand your data,
customers, & employees with
12X the speed and accuracy.
Visit: www.repustate.com to
learn more