Hey guys in this blog we will implement Youtube Comments Extraction and Sentiment Analysis in Python using Flask. It is going to be a very interesting project. So without any further due, let’s do it…
YouTube is one of the most popular video-sharing platforms in the world, with over 2 billion monthly active users. As a result, it generates a massive amount of data in the form of comments, which can provide valuable insights into the user’s opinion about a particular video or topic. In this article, we will discuss a project on YouTube comments extraction and sentiment analysis using Python and Flask.
Snapshots of our App
Home Screen

Results Screen

Wordcloud

Technology Stack
- Frontend – HTML and CSS
- Backend – Flask(Python)
Working of our Youtube Comments Extraction and Sentiment Analysis App…
- On the main page, we first enter/paste a youtube video url whose comments we need to analyze.
- Then we click on the ‘Analyse Comments‘ button.
- As soon as we hit the above button, our scrapper starts scraping comments from that video.
- Now that we have a list of all the scraped comments, we will then clean these comments and run a sentiment analysis model on these cleaned comments.
- A list of these cleaned comments along with their sentiment is sent on the results page.
- All the POSITIVE sentiment comments have a green background, all NEGATIVE sentiment comments have a red background and all NEUTRAL comments have a gray background.
- In the menu bar, we have a wordcloud option that will open up a wordcloud (as shown above) created accordingly from the scraped comments for a respective video.
Working Video of our App
About Source Code
As you know quality doesn’t come for free, so you have to pay a minimalistic fee for all those resources. If you are interested and want the source code of this application, you have to pay a minimalistic fee of ₹500 and send me the payment screenshot at asharma70420@gmail.com.
You can Pay using the button below…
NOTE:
If you face a similar error as shown below visit this link and follow the first answer.

So this is all for this blog folks. Thanks for reading it and I hope you are taking something with you after reading this and till the next time …
Read my last blog – Doctor-Patient Appointment System in Python using Flask
Check out my other machine learning projects, deep learning projects, computer vision projects, NLP projects, and Flask projects at machinelearningprojects.net.