Home About Login Current Archives Announcements Editorial Board
Submit Now For Authors Call for Submissions Statistics Contact
Home > Archives > Volume 20, No 5 (2022) > Article

DOI: 10.14704/nq.2022.20.5.NQ22658

Deep-Learned Bi-GRU-LSTM Model (DL-BGLM): A New Framework for Text-based Fake News Detection

Vegi A. Fernando and Ramesh K


In fields like democracy, commerce, and journalism, the news that are fake poses huge threat which leads to vast security damage. The authenticity of any news should be checked based on its contents. Many researchers have worked on this objective and achieved considerable performance. The proposed work gives a novel framework, Deep-Learned bi-GRU-LSTM Model (DL-BGLM) for detecting fake news by using text content and titleof the news by incorporating two new sub-frameworks. Performance analysis of the proposed work is carried out with other advanced text-based news datasets which shows better result.


Deep-Learned bi-GRU-LSTM Model, Fakenews detection, Deep Learning

Full Text