Sentiment Analysis is the use of Natural Language Processing, Text Analysis, Computational Linguistics and biometrics to systematically identify, extract, quantify and study affective states and subjective information.

The project deals with the analysis of articles that are scrapped from the link: https://asknkitkr.github.io/article/ The articles are send analyzed and it returns the Polarity of the article content as per condition:

if Polarity > 0.1: 
  return "Positive"
if Polarity < 0: 
  return "Negative"
if Polarity <= 0.1 and Polarity >= -0.1: 
  return "Neutral"

• beautifulsoup4
• requests
• urllib3
• textblob
• colorama
• prettytable

pip install -r requirements.txt

After installing all the required packages, open main2.py

• Ankit Kumar - https://github.com/asknkitkr
• Tushar Lohani - https://github.com/Tusharlohani
• Sakshi Kumari - https://github.com/sakshi413

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.