Online discussion platforms can face multiple challenges of abusive behaviour. In order to understand
the reasons for persisting such behaviour, we need to understand how users behave inside and outside
a community. In this paper, we propose a novel methodology to generate a dataset from offline and
online group discussion conversations. We advocate an empirical-based approach to explore the space of abusive behaviour. We conducted a user-study ( N = 15 ) to understand what factors facilitate
or amplify forms of behaviour in cases of online conversation that are less likely to be tolerated in
face-to-face. The preliminary analysis validates our approach to analyse large-scale conversation
dataset
