World Happiness Index based on News Sentiment

The project aims to calculate the World Happiness Index by analyzing news sentiment. By crawling news articles from various sources, performing sentiment analysis, and aggregating the sentiment scores, the project will provide insights into the happiness levels over time. The index will be derived from the sentiment scores, with positive news contributing to higher happiness scores and negative news affecting the index negatively. The project will also involve visualizing the calculated index using charts and graphs.

By working on this project, learners will enhance their Python programming skills while tackling real-world challenges. Additionally, learners will develop their problem-solving abilities and learn to effectively communicate their findings through documentation and presentations.

Skills you will develop:

1. Web Crawling: Learn how to crawl and extract data from news websites using Python.
2. Data collection and preprocessing: Gather news articles, clean and preprocess the text data for sentiment analysis.
3. Sentiment analysis: Implement sentiment analysis techniques to determine the sentiment polarity of news articles.
4. Data visualization: Use Python libraries like Matplotlib or Plotly to create charts and graphs for visualizing the calculated index.
5. Problem-solving: Address challenges related to data acquisition, sentiment analysis accuracy, and index calculation.
6. Project management: Plan, organize, and execute the project, adhering to deadlines and milestones.
7. Documentation and presentation: Document the project's methodologies, findings, and present the results in a clear and concise manner.