In the modern age, data is readily available everywhere on the internet. Therefore, it is a good idea to harness that data and generate useful information
What it does
Twitter-scraper fetches tweets related to a topic on Twitter and uses sentiment analysis to determine each tweets' opinion on the topic and then calculates the prevailing opinion on that topic by calculating the average of each tweets' sentiment value
How we built it
Challenges we ran into
Many team members have other work to attend to during the hackathon. Thus, we could not contribute a lot of development effort into the project.
Accomplishments that we're proud of
Despite the limited efforts we could contribute to the project, we were still able to build the project into a decent and complete product, with a relatively aesthetic frontend and a backend that completes the app specification with no errors.
What we learned
This is our first time working with React.js, so we learned about React. We also learned how important it is to plan personal activities carefully to not interfere with work
What's next for twitter-scraper
We are planning for new functionalities for twitter-scraper, including more advanced analytics on tweet data, more places to scrape data from, and perhaps some analytics functions specific to fintech and trading