https://github.com/chengetanaim/sentimentanalysisforfinancialnews

This is a Django application for predicting whether the sentiment of a financial news headline is positive, negative or neutral (from an investor point of view)
https://github.com/chengetanaim/sentimentanalysisforfinancialnews

beautifulsoup4 chartjs django html-css-javascript logistic-regression machine-learning natural-language-processing scikit-learn tfidf-vectorizer webscraping

Last synced: about 19 hours ago
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This is a Django application for predicting whether the sentiment of a financial news headline is positive, negative or neutral (from an investor point of view)

• Host: GitHub
• URL: https://github.com/chengetanaim/sentimentanalysisforfinancialnews
• Owner: Chengetanaim
• Created: 2023-08-16T08:43:21.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2023-08-19T08:45:11.000Z (about 1 year ago)
• Last Synced: 2024-01-27T19:01:21.373Z (9 months ago)
• Topics: beautifulsoup4, chartjs, django, html-css-javascript, logistic-regression, machine-learning, natural-language-processing, scikit-learn, tfidf-vectorizer, webscraping
• Language: CSS
• Homepage:
• Size: 1.54 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# SentimentAnalysisForFinancialNews

This is a Django application for predicting whether the sentiment of a financial news headline is positive, negative or neutral.


This project didn't focus on model building, the project for building the model is here - https://github.com/Chengetanaim/SentimentAnalysisForFinancialNewsNotebook


Web scraping tools were used to scrape financial data from the Financial Times website.

# What I Did/Learnt:

- loading the model for predicting sentiment of a financial news headline

- use web scraping tools to scrape data from the Financial Times website

- using named entity recognition to detect the main talked about countries in most financial news

- plotting interactive visualizations about sentiment and named entity recognition analytics using Chart js

# How to run the program

- Make sure you have python installed on your pc

- In the root folder of the project, run pip install -r requirements.txt using cmd or your text editor

- After the dependencies have been installed, run python manage.py runserver

- Copy the url provided and open it in your browser