About:
In this project, I developed a sentiment analysis pipeline to evaluate the sentiment of news articles related to stock markets. Using Python's Natural Language Toolkit (nltk) and other libraries, I processed text data, filtered duplicates, and performed sentiment analysis to classify articles as positive, negative, or neutral. The results were then plotted in a time series format to analyze the sentiment trends over time. This project allowed me to apply text processing and machine learning techniques to real-world financial data, providing valuable insights into the relationship between news sentiment and market behavior.