NITP-AI-NLP@UrduFake-FIRE2020: Multi-layer Dense Neural Network for Fake News Detection in Urdu News Articles

The last three runs are based on the binary classification task, where the first two (i.e., Run 4 and Run 5) are based on BoW with ma- jority voting and accumulative

Built around the idea reported in recent studies that the textual content can be helpful to identify fake news [5, 6], this shared task is aimed to explore the efficiency of models

Zhila, Data Augmentation using Machine Translation for Fake News Detection in the Urdu Language, in: Proceedings of the 12th Language Resources and Evaluation Conference, European

Our work is based on the dataset and the task provided by the organizers of 2020 Fake News Detection in the Urdu Language [6, 7].. Rest of the paper is organized

Fake news detection has recently fascinated a growing interest from the public and research community as the spread of unreliable information online increases, predominantly in

[3] have used Machine Translation (MT) to translate English fake news dataset consisting of 200 legitimate and 200 fake news [7] to Urdu and combined it with an original Urdu

Finally, the aim is to integrate the main tasks that interfere with the fake news detec- tion process with a contradiction detection module that can be used cross-sectionally

Abdullah, Automatic identi�cation of fake news using deep learning, in: 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS), IEEE,