You Tube Analytics And Sentiment Analysis

Abstract

1. Introduction

The repo consists of visualizations in D3.js (Observable) and Tableau for videos from YouTube's API for trending videos in the US. Refer to this repository to scrape data using the public API. The visualizations are created using raw statistics from the dataset, along with derived attributes like sentiment scores to gain more insight.

This is a cleaned version of the scraped data, and NLTK's SentimentAnalyzer is used to derive sentiment scores (ranging from -1 to 1) for videos, which are added to the CSV file as an additional feature.

Each entry in the dataset corresponds to trending videos (2020 to 2022) with features such as the title, trending date, published date, channel title, category, tags, description, views, likes, dislikes, comments, and comment count.

2. Objective

Interactive data visualizations for trending YouTube videos using Sentiment Analysis in D3.js and Tableau

This project demonstrates how JavaScript, Tableau can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/nirmal-25/YouTube-Analytics-and-Sentiment-Analysis.git
cd YouTube-Analytics-and-Sentiment-Analysis

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by nirmal-25 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.