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.
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