Implicitly Abusive Comparisons -- A New Dataset and Linguistic Analysis
We examine the task of detecting implicitly abusive comparisons (e.g. {``}Your hair looks like you have been electrocuted{''}). Implicitly abusive comparisons are abusive comparisons in which abusive words (e.g. {``}dumbass{''} or {``}scum{''}) are absent. We detail the process of creating a novel dataset for this task via crowdsourcing that includes several measures to obtain a sufficiently representative and unbiased set of comparisons. We also present classification experiments that include a range of linguistic features that help us better understand the mechanisms underlying abusive comparisons.
PDF AbstractTasks
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
