The price of a stock relies on a vast amount of data. At BoilerMake, we developed an application that web scrapes hundreds of news articles relevant to a company and utilizes sentiment analysis to engineer a new dimension to stock analysis. Few tools out there do what this application does, and the relevant ones that do exist lack the fundamental insights or features that bring an investment group beyond their current scope. This application allows a user to investigate the relationship of the online news community to draw relationships, connections, and offer explanations for shifts and changes in the market. More specifically, we decided to focus on an analysis of the company as a whole, and then the CEO's public perception. These two factors are compared against the perceived value of the stock on the market.
As a hackathon team, we focused on ensuring our features were well established and robust for any user. Show Me The Money scrapes a hundred news articles relevant to the company in real time, as well as stock information from the Bloomberg API. These news articles are then analyzed via a sentiment analysis tool and given a standardized score.
Furthermore, we focused on developing a clean and easy to use interface. The interface is very clear and provides the top 5 most negative and positive news articles, as well as recent articles about the website and a chart that makes it easy to compare trends between public sentiment and volume. It fosters exploration of potential or changing investment trends.
In the future, we hope to implement concurrency into our application by using a npm library known as cluster to help improve the scalability of analyzing large data sets of news articles.