A huge variety of social applications, such as Twitter and Instagram, have been developed over the last few decades. With the introduction of these online social networks, there has never been a better time to research human interaction on a worldwide scale. The goal of this project is to use a scalable and high-performance Twitter data visualization platform to investigate Twitter data on a given topic in real-time.
To create a scalable Twitter data visualization platform, we write a basic version of the system using the Twitter Developer Platform’s real-time and non-real-time APIs, optimize the frontend and backend performance with various components, and devise a benchmarking testing scheme to see if the application meets the scalability and high-performance requirements.
Our results demonstrate an improvement over the basic version, indicating that a scalable Twitter data visualization platform has been built. However, since it relies on Twitter API to collect data, it will be constrained by the rate limit of Twitter API.