YouTube Comment Sentiment Analysis to Unveil Public Opinion

What’s YouTube Comment Sentiment Analysis

YouTube comment sentiment analysis is the process of systematically extracting and interpreting emotions, opinions, and attitudes from user comments using computational tools.

Here are the primary sentiment categories:

• Positive: Expressions of approval, joy, or satisfaction.
• Negative: Expressions of disapproval, anger, or disappointment.
• Neutral: Objective statements without strong emotion.

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Why Is YouTube Sentiment Analysis Important

The importance of analyzing YouTube comment sentiment extends across multiple domains, including content creators, brands, marketers, and more.

For Content Creators

YouTube sentiment analysis is important for content creators. They are able to gain better insights into their audience’s preferences, reactions, and emotional engagement. If the negative comments are surging on their videos about some topics, this signals a need to address concerns in future content or clarify their perspective.

Conversely, positive comments can guide creators to double down on what resonates with their audience. Sentiment analysis also reflects fan loyalty. For example, consistent positive feedback indicates a dedicated fan base, while a sudden shift to negativity may warn of a public relations crisis.

For Brands and Marketers 

Some brands usually upload promotional videos for their products. Sentiment analysis can reveal whether comments praise the product’s ingredients or complain about its price. The sentiment data informs marketing strategies. You can adjust messaging to highlight strengths or address pain points.

How Do You Perform Sentiment Analysis on YouTube Comments

YouTube sentiment analysis brings many benefits no matter you are a content creator or a band. How do you analyze YouTube sentiment? Here are two YouTube sentiment analyzers that can help you without any trouble.

1. Streamlit

Streamlit is a real-time sentiment analyzer on YouTube comments. It can analyze up to 20,000 comments per video using the YouTube API. Just paste the YouTube link into the online tool, and you will get the sentiment results, including positive, negative, & neutral comments. Other details are included, such as the number of likes, total comments, and views.

For the sentiment analysis, Streamlit will generate a pie chart to see the sentiment distribution and a line chart to see the sentiment score. Plus, this free tool handpicked the top 5 positive and negative comments of the YouTube video.

Here’s how to use Streamlit to get sentiment analysis of YouTube video comments.

Step 1. Go to YouTube to copy the video link you want to analyze the comment sentiment.

Step 2. Visit https://youtube-comment-sentiment-analysis-3rfvhjvsmup6n2im8nzerd.streamlit.app/.

Step 3. Paste the video link into the address box and click on Analyze.

All the comment sentiment analysis results will appear.

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2. YouTube Comment Analyzer

YouTube Comment Analyzer is an advanced extension tool designed to help YouTube content creators and marketers analyze, understand, and engage with their audience effectively. Powered by AI, this extension provides detailed insights into viewer comments and automatically categorizes comments into positive, neutral, or negative. It gives you a quick overview of audience feedback.

In addition, YouTube Comment Analyzer can easily summarize feedback, address questions, and generate ideas for future content. Then, download all analyzed data in a CSV file for detailed reporting and further use.

What you should pay attention to is that you need to analyze the sentiment more times to get accurate data. Here’s how to use YouTube Comment Analyzer.

Step 1. Visit https://chromewebstore.google.com/detail/youtube-comment-analyzer/fhdadknjmpgbibbeknkeelkfbckhlmen and download and enable this extension.

Step 2. Go to YouTube and scroll through the comments section of the YouTube video.

Step 3. Click the Analyze Sentiment button to process visible comments.

Step 4. After that, you can see the numbers of positive, neutral, and negative. Click on Export to CSV for reports and analysis.

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Bottom

YouTube comment sentiment analysis can interpret these emotions, opinions, and attitudes from user comments, making it an indispensable part of understanding the digital world. Streamlit and YouTube Comment Analyzer are great tools for analyzing sentiment for YouTube comments.