Facebook sentiment analysis is the automated process of understanding a person’s opinion about a particular subject based on a comment or post. When you can’t figure out the emotion that fueled a customer’s written response, you run the risk of staring at the same words for hours on end. Thankfully, that’s where sentiment analysis comes in. Using AI technology, sentiment analysis can interpret customer’s feelings by using natural language processing models.

2. Facebook Sentiment
Analysis - Posts &
Comments
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3. Table of Content
● How Does Sentiment Analysis of Facebook Posts Work?
● Repustate’s Sentiment Analysis Dashboard
● How Can You Choose The Best Sentiment Analysis Tool for
Facebook Posts?
● What Are the Benefits of Using Sentiment Analysis for
Facebook?

4. Overview
Facebook sentiment analysis is the automated process of
understanding a person’s opinion about a particular subject based
on a comment or post. When you can’t figure out the emotion that
fueled a customer’s written response, you run the risk of staring at
the same words for hours on end. Thankfully, that’s where
sentiment analysis comes in. Using AI technology, sentiment
analysis can interpret customer’s feelings by using natural language
processing models.

5. How Does Sentiment Analysis of Facebook
Posts Work?

7. Repustate’s Sentiment Analysis Dashboard

9. How Can You Choose The Best Sentiment
Analysis Tool for Facebook Posts?

10. The best Facebook sentiment analysis tool should be accurate, quick, and scalable, as it
analyses thousands of comments through social media listening. It should understand
different languages while interpreting accurate sentiment scores for each entity
extracted. This is possible only if it knows each language natively, like Repustate’s
solution does, without the need for translations.
Below are ten essential requirements the best Facebook sentiment analysis tool should
have.
● Speed and Scale: The sentiment analysis solution should be able to process at least
500 posts per second, and scale to more than 100,000+.
● Accuracy: This is an important aspect that is needed to truly gauge sentiment. As a
model is trained, the accuracy scores increase, but what is also important is that
accuracy is maintained as the data scales.
● Aspect-Based Analysis: The sentiment analysis model needs to robustly extract
aspects from entities and topics and analyse them for emotions. Only then can you
get the most granular customer insights.

11. What Are the Benefits of Using Sentiment
Analysis for Facebook?

12. Facebook is one of the largest social media networks in the world. It allows you to
connect with current customers and potential leads. You can use user-generated
content to continue improving your business, and stay on top of new trends. With
sentiment analysis on facebook, you can:
● Keep Tabs on Your Brand Reputation: Sentiment analysis can chart customers’
feelings for your products or services so you can observe growth over time
● Avoid Negative PR: Analysing sentiment can warn you if something negative
associated with your brand pops up, so you aren’t caught backtracking when
it’s too late
● Offer Better Customer Service: People usually only post about things they
really love or hate, so if someone posts a negative review, you’ll have the
opportunity to review what you can improve. Learn how Amazon review
analysis is helping companies offer better customer service.

13. Thank you!
Understand your data,
customers, & employees with
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