Topic Modeling for Twitter Accounts

Makers, scientists, influencers and many other people share their ideas, products and innovations via the most intellectual social network Twitter. It is hard to find the information about a topic in the giant network of Twitter. Our aim is to find users who are tweeting about the same topic. With this aim we want to bring people interested in the same community together. In this project, we focused on maker communities and influencers in the context of computer science, such as ML, Robotics, 3D Printing, Arduino. We considered each twitter account as a document which includes tweets of this account and used topic modeling algorithms such as Latent Dirichlet Allocation and Non-Negative Matrix Factorization to determine what accounts are talking about.  We worked on 1.118 Twitter users and approximately 3.250.000 tweets.