YouTube Comments Sentiment Analysis

Analyze sentiment in YouTube video comments using R

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📌 Overview

This project performs sentiment analysis on comments retrieved from a YouTube video using R programming and YouTube Data API v3. It fetches comments based on a video ID, cleans and processes the text, and classifies them as positive or negative using lexicon-based sentiment scoring.

Ideal for:

• 🎥 YouTubers or marketers analyzing viewer response
• 📈 Researchers studying social sentiment trends
• 🧠 Students exploring real-world NLP using R

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✨ Features

• 🔑 Fetch comments using YouTube Data API
• 🧹 Text preprocessing (tokenization, stopwords removal, etc.)
• 📊 Lexicon-based sentiment classification
• 📈 Sentiment summary with visualizations (bar plot, pie chart, word cloud)
• 📁 Option to export results to CSV

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🛠️ Tech Stack

Component	Technology
Language	R
Text Mining	tidytext, tm
API Integration	youtube comments API
Visualization	ggplot2, wordcloud
Data Wrangling	dplyr, tidyr

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🚀 Getting Started

Get Your API Key

• Go to Google Cloud Console
• Enable YouTube Data API v3
• Generate an API Key
• Update the following line with your API key and video ID:

  api_key <- "YOUR_YOUTUBE_API_KEY"
  video_id <- "YOUR_VIDEO_ID"