The lack of information coming into investing makes it hard for a user to determine what stocks are good choices to buy.
What it does
Our app gives users a indepth informational guide on their chosen stock. After a user registers and logs in, a user is shown their stock list. Our program searches the internet for recent news article using stock keywords. The data is then processed using a sentiment analysis natural language processor. A sentiment analysis on the text provides a numerical outcome on the positivity of the article this number is shown from -1, 1 where -1 is negative and 1 is positive. This output is then displayed to the user to advise them on whether to buy it or not.
How we built it
We used android studio to make the app and design its layout. In order to incorporate the webscraping from the news sites and the sentiment analysis on this scraped data, we need to use two different api's. The first is newsapi, used in webscraping, and the last one is ibm-watson, which we used for sentiment analysis.
Challenges we ran into
Since the api's ran in python, we needed to use retrofit to send a request from our program to their api. Understanding and using the retrofit code was difficult, but we managed to make it work.
Accomplishments that we're proud of
We're proud of how the app turned out and that it functions properly and how it is intended.
What we learned
In the future, more time should be allotted to the incorporation of the api's in our app since this is what proved to take up the most time.
What's next for Stock chasers
We will work on making the app more visually appealing and user friendly.
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