BlogMe Sentiment Analysis

This Python project performs sentiment analysis on articles from the BlogMe platform using VADER sentiment intensity analyzer. The analysis includes counting articles, reactions by publisher, dropping unnecessary columns, and extracting sentiment scores for article titles.

Getting Started

Prerequisites

• Python 3.x
• Install required packages by running: i. pip install pandas vaderSentiment
• Download the sample dataset or replace 'articles.xlsx' with your dataset. Run the Python script: i. python sentiment_analysis.py ii. View the results in the 'blogme_clean.xlsx' file.

Features

Counting Articles per Source:

Analyze the number of articles per source.

Reactions by Publisher:

Calculate the total engagement reaction count for each publisher.

Keyword Finding:

Use loops to find specific keywords in article titles.

Sentiment Analysis:

Extract sentiment scores (negative, neutral, positive) for article titles.

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