Inspiration
We were inspired by Majestic, who provided us with their great API.
What it does
The application interprets Twitter users' opinions on different topics of your choice. It searches for tweets related to your keyword, selects the most popular ones using the Majestic API and analyses them using Google's Natural Language Processing API. We are showing the general opinion of the people and the most frequently used adjectives when talking about the respective topic. It can also analyse a user's Twitter activity, showing information about patterns in his tweets and his overall attitude when posting, as well as the number of links pointing to his profile.
How we built it
We built the back end API in Python and Node.js, which is called on the client side using html, css and angularjs. We used external APIs like Twitter's REST, Google's Natural Language Processing and Majestic API.
Challenges we ran into
Putting all these technologies together and making sure they cooperate effectively is a difficult task.
Accomplishments that we're proud of
We are proud of managing to interpret all this information and to visualise it in a nice way.
What we learned
We got an insight into data analysis and natural language processing.
What's next for AskTwitter
We plan on finding new ways of using Google's and Majestic's data and refining the application.
Built With
- python
- flask
- angular.js
- google-natural-language-processing-api
- html
- css
- node.js
- javascript
- majestic-api
Log in or sign up for Devpost to join the conversation.