online-news-popularity-analysis

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online-news-popularity-analysis

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Exploratory Data Analysis of Online News Popularity using Python to identify key factors influencing news engagement.

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# online-news-popularity-analysis
Exploratory Data Analysis of Online News Popularity using Python to identify key factors influencing news engagement.

# Project Overview

This project focuses on analyzing the factors that influence online news engagement using data science techniques. The dataset consists of over 39,000 news articles with features related to content, keywords, sentiment, and publishing time.

# Objectives

* To perform Exploratory Data Analysis (EDA)
* To identify key factors affecting news popularity
* To visualize patterns using graphs
* To apply a basic machine learning model

# Key Insights

* News engagement is highly right-skewed
* Articles with more images tend to receive more shares
* Weekend publishing increases engagement
* Keyword popularity has a positive impact

# Technologies Used

* Python
* Pandas
* NumPy
* Matplotlib
* Seaborn
* Scikit-learn

# Files Included

* Jupyter Notebook (.ipynb)
* Project Report (PDF)
* Graph Images

# Acknowledgment

I would like to thank my mentor/class instructor Veerpal Kaur for their valuable guidance and support.

# Dataset Source

UCI Machine Learning Repository

online-news-popularity-analysis

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