# BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts

arXiv: https://arxiv.org/abs/2205.08868 · HTML: https://mlsanity.com/paper/2205.08868/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 11 references that are in the map.
- First posted on arXiv 18 May 2022.

## Builds on (most cited first, 2 of 2)

- [Irony Detection in a Multilingual Context](https://mlsanity.com/paper/2002.02427/) (2020)
- [Improving Sentiment Analysis in Arabic Using Word Representation](https://mlsanity.com/paper/1803.00124/) (2018)

## Abstract (arXiv)

This paper describes the systems submitted to iSarcasm shared task. The aim of iSarcasm is to identify the sarcastic contents in Arabic and English text. Our team participated in iSarcasm for the Arabic language. A multi-Layer machine learning based model has been submitted for Arabic sarcasm detection. In this model, a vector space TF-IDF has been used as for feature representation. The submitted system is simple and does not need any external resources. The test results show encouraging results.