Transfer Learning with Augmented Vocabulary for Tweet Classification : (Grand Challenge)

In this paper, we describe our experiments and insights gathered in the process of participating in the BigMM Grand Challenge 2020, where the task was to classify a set of tweets pertaining to the #MeToo movement into five linguistic aspects. We analyzed the data set and experimented with several approaches, including classical machine learning models and state of the art deep learning architectures. We achieved our best results by applying transfer learning on a pre-trained ULMFiT model. Our best performing approach had ranked first on the leader-board when the grand challenge finished.