YouTubeAlgoAnalyser - BitBusters - TataPowerHackathon

First Place winning project in Problem Statement track 2 at the Tata Power Hackathon Hosted by Mindspark in 2023

Project Overview

YouTubeAlgoAnalyser is a web application designed to assist YouTube content creators focused on "Environment and Sustainable development" in improving their SEO strategies. By leveraging the YouTube Data API, data mining algorithms, and various analytical tools, our project offers a comprehensive set of insights, features and recommendations:

Key Features

1. Data Mining: The project utilizes data mining algorithms we built in Python to extract and analyze data from the YouTube Data API. This data includes video statistics, comments, and metadata.

2. Topic Insights: Our platform generates insights into how the YouTube algorithm ranks video topics related to "Environment and Sustainable development." This information is invaluable for content creators looking to optimize their content.

3. Hashtag Analysis: The system identifies the most commonly used hashtags in top-performing videos within a specific topic. This helps content creators understand which hashtags can boost the discoverability of their videos.

4. Likes, Comments and Views Analytics: For popular sustainable energy topics, our project calculates the average number of likes, comments and views providing content creators with a reference point for expected engagement.

5. Trend Analysis: The project employs DBSCAN and Hyperopt for auto cluster labeling, enabling content creators to understand emerging trends in the field.

6. Sentiment Analysis: Using NLTK VADER, our platform offers sentiment analysis for video comments, helping content creators gauge audience reactions and feelings.

7. Word Clouds: Word clouds are generated from comment text, providing an intuitive visualization of the most discussed topics within the comments.

8. Video Statistics: Content creators can input a video URL to analyze statistics such as likes, comments, favorites, views, and more. This feature helps them monitor video performance.

9. User Behavior Analysis: Your project also delves into analyzing the viewing habits of users who comment on videos, shedding light on the other content topics that they engage with.

10. Interactive Data Visualization: Frontend components are powered by Plotly and the WordCloud library, making it easy for users to visualize and understand the data.

Technologies:

1. Data Extraction and User Behaviour Analysis: YouTube Data API v3​, Python
2. Sentiment and Knowledge Analysis: NLTK, WordCloud, Plotly and Matplotlib
3. Trend Analysis:​ Sklearn DBSCAN, HuggingFace, Hyperopt

Contributors

• Harshawardhan Deshmukh
• Atharva Mutsaddi
• Himanshu Kamdi
• Vaishnavi Badgujar

Acknowledgments

We would like to thank Tata Power and COEP Mindspark for hosting this hackathon and providing a platform for innovative projects like YouTubeAlgoAnalyser. We are also grateful to the YouTube Data API for making this project possible.

Thank you for considering our project, and we hope it brings value to the YouTube content creator community in the "Environment and Sustainable development" niche. If you have any questions or need further assistance, please feel free to reach out to our team.