Kanye West Tweets - Sentiment Analysis

Table of Contents

• Kanye West Tweets - Sentiment Analysis
  • Table of Contents
  • Introduction
  • Project Overview
  • Examples
  • Data Collection
  • Data Preprocessing
  • Sentiment Analysis
  • Emotions Analysis
  • Dependencies
  • Usage
  • Contributing
  • License

Introduction

This repository contains a Natural Language Processing (NLP) project that focuses on analyzing the sentiment of tweets related to Kanye West. Sentiment analysis is the process of determining the emotional tone behind a piece of text, which can be useful for understanding public opinion, market research, and more.

Project Overview

In this project, we will perform sentiment analysis on a dataset of tweets related to Kanye West. We will classify each tweet as positive, negative, or neutral, providing insights into how the public perceives Kanye West on Twitter.

Examples

Here are some examples of tweets that we will analyze:

• "I miss the old Kanye, straight from the Go Kanye"
• "I hate the new Kanye, the bad mood Kanye"
• "I love you like Kanye loves Kanye"
• 

Data Collection

To perform sentiment analysis, we need a dataset of Kanye West tweets. We will scrape Twitter data using Python libraries such as Tweepy and BeautifulSoup. Ensure that you have the necessary access to Twitter's API to collect tweets.

Data Preprocessing

Before conducting sentiment analysis, we will preprocess the collected tweets. This includes:

• Removing special characters, URLs, and hashtags.
• Tokenizing and lemmatizing the text.
• Handling missing data.
• Removing duplicates.

Sentiment Analysis

We will use Natural Language Processing techniques to classify the sentiment of each tweet into one of the following categories:

• Positive
• Negative
• Neutral

We will use a pre-trained NLP model for sentiment classification or train our own model, depending on the size and quality of the dataset.

Emotions Analysis

We will also perform emotions analysis on the tweets. We will use a pre-trained NLP model for emotions classification or train our own model, depending on the size and quality of the dataset.

• 

Dependencies

Make sure you have the following dependencies installed:

• Python 3.x
• Tweepy (for data collection)
• BeautifulSoup (for web scraping)
• Natural Language Toolkit (NLTK) or spaCy (for text preprocessing)
• Scikit-learn (for machine learning)
• Jupyter Notebook (optional for data exploration and visualization)

You can install these dependencies using pip:

pip install tweepy
pip install beautifulsoup4
pip install nltk
pip install scikit-learn
pip install jupyter

Usage

To run the project, you can clone the repository locally and run the Jupyter Notebook file:

git clone
cd kanye-west-tweets-sentiment-analysis
jupyter notebook

Contributing

Contributions are welcome! For bug reports or requests please submit an issue.

License

This project is licensed under the MIT License.