Youtube Comments Extraction and Sentiment Analysis Flask App — with source code

Published in

MLearning.ai

3 min readMar 16

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.

Read the full blog here — https://machinelearningprojects.net/youtube-comments-extraction-and-sentiment-analysis/

Checkout the Video here

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.