# UrduFake@FIRE2020: Shared Track on Fake News Identification in Urdu

arXiv: https://arxiv.org/abs/2207.12406 · HTML: https://mlsanity.com/paper/2207.12406/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 11 references that are in the map.
- First posted on arXiv 25 Jul 2022.

## Builds on (most cited first, 1 of 1)

- [Mining Dual Emotion for Fake News Detection](https://mlsanity.com/paper/1903.01728/) (2019)

## Abstract (arXiv)

This paper gives the overview of the first shared task at FIRE 2020 on fake news detection in the Urdu language. This is a binary classification task in which the goal is to identify fake news using a dataset composed of 900 annotated news articles for training and 400 news articles for testing. The dataset contains news in five domains: (i) Health, (ii) Sports, (iii) Showbiz, (iv) Technology, and (v) Business. 42 teams from 6 different countries (India, China, Egypt, Germany, Pakistan, and the UK) registered for the task. 9 teams submitted their experimental results. The participants used various machine learning methods ranging from feature-based traditional machine learning to neural network techniques. The best performing system achieved an F-score value of 0.90, showing that the BERT-based approach outperforms other machine learning classifiers.