Work

AU_NLP at SemEval-2023 Task 10: Explainable Detection of Online Sexism Using Fine-tuned RoBERTa

Year: 2023

Type: conference-paper

Abstract: Social media is a concept developed to link people and make the globe smaller.But it has recently developed into a center for sexist posts that target especially women.As a result, there are more events of hostile actions and harassing remarks present online.In this paper, we introduce our system for the task of Explainable Detection of Online Sexism (EDOS), a part of SemEval 2023 task 10.We introduce a finetuned RoBERTa model by encoding the initial representation of the data using Roberta and setting three distinct Multilayer Perceptrons (MLPs) corresponding to the three sub-tasks to address this specific problem.The effectiveness of the proposed strategy is demonstrated by the experimental results reported in this research.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/2023.semeval-1.97

Authors: Amit Das, Nilanjana Raychawdhary, Tathagata Bhattacharya, Gerry Dozier, Cheryl D. Seals

Institutions: Auburn University, Auburn University at Montgomery

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Reduced inequalities, Gender equality

Open Access status: hybrid

OpenAlex ID: W4385572385