Stock Price Prediction with Sentiment Analysis

Inspiration

I think incorporating sentiment analysis and stock prices are fun, and news articles can definitely be good indicators on how a particular stock performs.

What it does

This App pulls the latest 10 news and analyze them with a Natural Language Toolkit with a wordbank updated to better capture finance sentiments. Then it generates a pie chart of the percentage of positive, negative, and neutral sentiment, and then generates a wordcloud of the news article.

How we built it

I used the Anvil platform to make my Web App based on python

Challenges we ran into

It took me a while to get used to Anvil. Since it's a free platform, I couldn't use the python libraries I had access to on my computer. Eventually I learned how to use uplink modules and that helped a lot.

Accomplishments that we're proud of

Even though there is a lot of things I wish I could have added to the App (better UI, deeper analysis of the data, and maybe some statistical analysis of historical stock prices), I'm proud of the fact that I got used to this brand new platform and learned to adapt. This is my first time to make a Web App all by my own, and I hope I can do more with this concept in the future

What we learned

I learned a lot about how to use APIs, how to write files, and how to use data tables; and of course, how to navigate an online platform to build my App

What's next for Stock Price Prediction with Sentiment Analysis

I hope I can incorporate a more detailed analysis on the news articles and make more visualizations; I also would like to predict stock prices with historical price data through time series.

Built With

• anvil
• python