/Sentiment-Analysis-in-Financial-Markets

Analyze news articles, financial reports to gauge market sentiment. This project would involve natural language processing (NLP) techniques to understand how sentiment affects stock prices.

Primary LanguageJupyter Notebook

Sentiment Analysis in Financial Markets

Overview

This project utilizes Natural Language Processing (NLP) techniques to analyze sentiments in financial markets through news articles, financial reports, and social media to understand the impact on stock prices and market trends.

Prerequisites

  • Python 3.6 or higher
  • Pip

Usage

To use this project:

  1. Execute data collection scripts in the data_collection folder.
  2. Run data preprocessing scripts in the data_preprocessing folder.
  3. Perform sentiment analysis by running the sentiment_analysis.py script.

Built With

  • Python - The core programming language used.
  • Pandas - The library used for data manipulation and analysis.
  • BERT - Used for processing textual data.

Project Status

Ongoing

Authors