SOTAVerified

Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse

2021-08-01ACL (WOAH) 2021Code Available0· sign in to hype

Ravsimar Sodhi, Kartikey Pant, Radhika Mamidi

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Online abuse and offensive language on social media have become widespread problems in today’s digital age. In this paper, we contribute a Reddit-based dataset, consisting of 68,159 insults and 51,102 compliments targeted at individuals instead of targeting a particular community or race. Secondly, we benchmark multiple existing state-of-the-art models for both classification and unsupervised style transfer on the dataset. Finally, we analyse the experimental results and conclude that the transfer task is challenging, requiring the models to understand the high degree of creativity exhibited in the data.

Tasks

Reproductions