Every day there is an innumerable number of news articles posted about stocks. No investor should be expected to be able to read all these various articles in order to get an assessment of how a company's stocks are being viewed on the market. Ideally, our hack can solve this problem by giving users an accurate feel for the current perception of companies they are interested in and make their investment decisions accordingly.

We have created a website that gathers aggregate data from various news articles located on Alpha Seeks and Marketwatch. This data is fed into google cloud natural language processing and sentiment analysis is performed, informing the user if the latest news for companies on the stock market is positive or negative. Also, the user will also be able to view the companies current stock price, as well as if the stock has been positive or negative compared to its price from a week ago. Based on this data a user can determine if a stock is seen as a buy or sell.

We divided into two teams, the front end and back end. The back end team created a web scraping program that is able to take data from various articles based on keywords and puts them into a list. Sentiment analysis is then performed on these articles. The front end team created a website and designed the implementation of the connection of the data from the web scraper to the website.

Some challenges we ran into were deploying flask, finding APIs that we had access to, many syntax errors, connecting the front end and the back end among others.

The accomplishments that we are most proud of are creating are the web scraping program and that our website is able to be deployed for demonstration.

We learned about web-scraping, using flask for web development, google cloud, and finance.

News Market Value hopes to take skills learned from this hack and apply it to a new project in the fintech space.

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