  The rapid integration of the Internet into our daily lives has led to many
benefits but also to a number of new, wide-spread threats such as online hate,
trolling, bullying, and generally aggressive behaviours. While research has
traditionally explored online hate, in particular, on one platform, the reality
is that such hate is a phenomenon that often makes use of multiple online
networks. In this article, we seek to advance the discussion into online hate
by harnessing a comparative approach, where we make use of various Natural
Language Processing (NLP) techniques to computationally analyse hateful content
from Reddit and 4chan relating to the 2020 US Presidential Elections. Our
findings show how content and posting activity can differ depending on the
platform being used. Through this, we provide initial comparison into the
platform-specific behaviours of online hate, and how different platforms can
serve specific purposes. We further provide several avenues for future research
utilising a cross-platform approach so as to gain a more comprehensive
understanding of the global hate ecosystem.
