|
|
|
|
|
Jawaher Alghamdi, Yuqing Lin and Suhuai Luo
The detection of fake news has emerged as a crucial area of research due to its potential impact on society. In this study, we propose a robust methodology for identifying fake news by leveraging diverse aspects of language representation and incorporati...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andra Sandu, Ioana Ioana?, Camelia Delcea, Laura-Madalina Geanta and Liviu-Adrian Cotfas
The proliferation of misinformation presents a significant challenge in today?s information landscape, impacting various aspects of society. While misinformation is often confused with terms like disinformation and fake news, it is crucial to distinguish...
ver más
|
|
|
|
|
|
|
|
|
|
|
Marian Bucos and Bogdan Dragulescu
Misinformation poses a significant challenge in the digital age, requiring robust methods to detect fake news. This study investigates the effectiveness of using Back Translation (BT) augmentation, specifically transformer-based models, to improve fake n...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chenbo Fu, Xingyu Pan, Xuejiao Liang, Shanqing Yu, Xiaoke Xu and Yong Min
In recent years, fake news detection and its characteristics have attracted a number of researchers. However, most detection algorithms are driven by data rather than theories, which causes the existing approaches to only perform well on specific dataset...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fawaz Khaled Alarfaj and Jawad Abbas Khan
The online spread of fake news on various platforms has emerged as a significant concern, posing threats to public opinion, political stability, and the dissemination of reliable information. Researchers have turned to advanced technologies, including ma...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jing Chen, Gang Zhou, Jicang Lu, Shiyu Wang and Shunhang Li
Fake news detection has become a significant topic based on the fast-spreading and detrimental effects of such news. Many methods based on deep neural networks learn clues from claim content and message propagation structure or temporal information, whic...
ver más
|
|
|
|
|
|
|
|
|
|
|
Richard G. Mayopu, Yi-Yun Wang and Long-Sheng Chen
Recent studies have indicated that fake news is always produced to manipulate readers and that it spreads very fast and brings great damage to human society through social media. From the available literature, most studies focused on fake news detection ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jawaher Alghamdi, Yuqing Lin and Suhuai Luo
The prevalence of fake news on social media has led to major sociopolitical issues. Thus, the need for automated fake news detection is more important than ever. In this work, we investigated the interplay between news content and users? posting behavior...
ver más
|
|
|
|
|
|
|
|
|
|
|
Faizi Fifita, Jordan Smith, Melissa B. Hanzsek-Brill, Xiaoyin Li and Mengshi Zhou
The spread of fake news related to COVID-19 is an infodemic that leads to a public health crisis. Therefore, detecting fake news is crucial for an effective management of the COVID-19 pandemic response. Studies have shown that machine learning models can...
ver más
|
|
|
|
|
|
|
|
|
|
|
Husam M. Alawadh, Amerah Alabrah, Talha Meraj and Hafiz Tayyab Rauf
Internet use resulted in people becoming more reliant on social media. Social media have become the main source of fake news or rumors. They spread uncertainty in each sector of the real world, whether in politics, sports, or celebrities? lives?all are a...
ver más
|
|
|
|
|
|