Multi-level stacked ensemble learning for identifying hate speech spreaders on Twitter

Abstract

There are growing signs of discontent with the anti-social behavior expressed on social media platforms. Harnessing the power of machine learning for the purpose of detecting and mediating the spread of malicious behavior has received a heightened attention in the last decade. In this paper, we report on an experiment that examines the predictive power of a number of sparse and dense feature representations coupled with a multi-level ensemble classifier. To address the research questions, we have used PAN 2021 Profiling Hate Speech Spreaders on Twitter task for English language. The initial results are encouraging pointing out to the robustness of the proposed model when evaluated on the test dataset.