TEDx Talks Analysis 🕵️‍♂️📜

Welcome to the TED Talk Transcript Analysis project! This repository contains an end-to-end analysis of TED Talk transcripts using R, AI, and Quarto for documentation.

🔎 Project Overview

This project focuses on analyzing TED Talk transcripts to uncover key insights, such as prevalent topics, opinion strengths, and thematic trends. The analysis leverages R for data processing, AI models for topic prediction and sentiment analysis, and Quarto to create an engaging, interactive report.

🚀 Key Features:

• Data Processing: Cleaning and preprocessing transcript data.
• Topic Modeling: Using AI techniques to identify and categorize key themes.
• Opinion Strength Analysis: Evaluating how strongly speakers align with various topics.
• Visualization: Interactive charts created with Plotly and DT tables for dynamic data exploration.
• Quarto Documentation: Seamlessly integrates code, text, and visuals into an interactive HTML report.

🛠️ Technologies Used:

• R: Data manipulation and analysis.
• Plotly: Generating dynamic and interactive visualizations.
• Quarto: Creating reproducible and shareable reports.
• MongoDB: (Optional) For reading data from a database source.
• AI Models: Implemented for topic prediction and sentiment analysis.

▶️ How to Run the Project:

1. Clone the Repository:

   git clone https://github.com/Soumyadipta2020/ted_talks_analysis.git
   cd ted_talks_analysis

2. Install Required Packages:

   install.packages(c("dplyr", "DT", "plotly", "jsonlite", "httr2"))

3. Render document

📂 Project Structure:

• data/: Contains the sample transcript CSV file.
• Analysis.qmd: Quarto file for the analysis report.
• helper.R, mongodb_helper.R: Custom helper functions.
• api.R (Not present here) : API key mentioned.
• README.md: Project documentation.
• manifest.json: Environment captured.

💡 Contribution:

Contributions are welcome! If you have ideas to enhance the app or fix issues, feel free to fork the repository, make changes, and submit a pull request.

Steps to Contribute:

1. Fork this repository.
2. Create a new branch: git checkout -b feature-name
3. Commit your changes: git commit -m "Add feature-name"
4. Push to your branch: git push origin feature-name
5. Open a Pull Request.

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Happy Analyzing! 🎤📊