The Problem of Fraudulent Content on the Web: Deep Learning Approaches

With the fast pace of life and advancement in technology, people rely more on social networking sites for the happenings around the globe. The misinformation or rumors spread across especially during emergency situations such as Pulwama Attack 2019 or The Attack of 26/11 or a natural calamity like the Kerala Flood 2018 can have a devastating effect on individuals and society. Spurious news in such a scenario would not only give rise to panic among the individuals but in some cases, it may also target a particular community. In this paper, we try to understand the term Spurious news in more detail and analyze the situation of Spurious news in India in a broader manner. We will also review the various state-of-the-art techniques that exist for solving the fraudulent news problem from different aspects such as deep learning, machine learning, etc.

Keywords: Spurious News, Rumor, Deep Learning, Machine Learning

Suggested Citation: Suggested Citation

Meel, Priyanka and Bano, Farhin and Vishwakarma, Dr. Dinesh K., The Problem of Fraudulent Content on the Web: Deep Learning Approaches (April 14, 2020). Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence (ICAEEC) 2019, Available at SSRN: https://ssrn.com/abstract=3575411 or http://dx.doi.org/10.2139/ssrn.3575411