# RiTUAL-UH at TRAC 2018 Shared Task: Aggression Identification

arXiv: https://arxiv.org/abs/1807.11712 · HTML: https://mlsanity.com/paper/1807.11712/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jul 2018.

## Built on by (most cited first, 3 of 3)

- [Hater-O-Genius Aggression Classification using Capsule Networks](https://mlsanity.com/paper/2105.11219/) (2021)
- [Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language](https://mlsanity.com/paper/2110.09393/) (2021)
- [A Survey on Online User Aggression: Content Detection and Behavioral Analysis on Social Media](https://mlsanity.com/paper/2311.09367/) (2023)

## Abstract (arXiv)

This paper presents our system for "TRAC 2018 Shared Task on Aggression Identification". Our best systems for the English dataset use a combination of lexical and semantic features. However, for Hindi data using only lexical features gave us the best results. We obtained weighted F1- measures of 0.5921 for the English Facebook task (ranked 12th), 0.5663 for the English Social Media task (ranked 6th), 0.6292 for the Hindi Facebook task (ranked 1st), and 0.4853 for the Hindi Social Media task (ranked 2nd).