This project is designed to use Sentiment Analysis to understand the if the financial news of a company depict positive or negative prospects for the company.
There are millions of articles posted on stocks - each article has the power to dramatically change the share price of that company.
Rather than individually going through each article, this system parses through thousands of articles available online and predicts if the news represents positive or negative updates for any given company listed on the Australian or American Stock Exchange.
I developed this project because I personally spend a lot of time doing market research and reading through news articles. Hence, I was in search for an automated process which could tell me if the news which are published about a company I hold or want to buy are positve or negative. This would help me better understand the market sentiment around a company I am researching.
Programming Language: Python 3
Libraries
- BS4 (BeautifulSoup) -> Used for Web Scrapping
- Pandas -> Used for accessing data structures to store the data
- MatPlot -> Used to produce visualisations of the results
- nltk -> Used to implement the Sentiment Analyzer