BlogMe Article and Sentiment Analysis

BlogMe, a renowned blogging business, possesses a dataset of news articles requiring in-depth analysis. Their primary objectives include extracting keywords from article headlines and determining the sentiment of the news articles, categorizing them as Positive, Negative, or Neutral. The data is currently stored in an Excel sheet, and BlogMe aims to create a dashboard illustrating sentiments, top articles, and more.

By leveraging Tableau and Vader Sentiment analysis in Python, the dashboard has been developed to visually represent the analysis based on the aforementioned requirements. Key components of the solution are outlined below:

1. Number of Engagements by Published Date
2. Top Titles with Negative Sentiment based on Total Engagement
3. Total Engagements of Articles Mentioning “Murder” (as a top negative sentiment)
4. Sources Ranked by Total Engagement (CNN, BBC, Al-Jazeera)