Results 31 to 40 of about 53,226 (249)

OPCNN-FAKE: Optimized Convolutional Neural Network for Fake News Detection [PDF]

IEEE Access, 2021
Recently, there is a rapid and wide increase in fake news, defined as provably incorrect information spread with the goal of fraud. The spread of this type of misinformation is a severe danger to social cohesiveness and well-being since it increases political polarisation and people’s distrust of their leaders.
Hager Saleh, Abdullah Alharbi, Saeed Hamood Alsamhi   +2 more
openaire   +3 more sources

Long-Short-Term Memory Model for Fake News Detection in Nigeria

Ianna Journal of Interdisciplinary Studies, 2023
Background: The advent of technology allows information to be passed through the Internet at a breakneck speed and enables the involvement of many individuals in the use of different social media platforms.
Adebimpe Esan, Olayinka Abodunrin, Adedayo Sobowale, Ibrahim Adeyanju, Nnamdi Okomba, Bolaji Omodunbi, Tomilayo Adebiyi, Janet Jooda, Taofeek Abdul- Hameed , Opeyemi Asaolu   +9 more
doaj   +2 more sources

Credibility-Based Fake News Detection [PDF]

, 2020
Fake news can significantly misinform people who often rely on online sources and social media for their information. Current research on fake news detection has mostly focused on analyzing fake news content and how it propagates on a network of users. In this paper, we emphasize the detection of fake news by assessing its credibility.
Sitaula, Niraj, Mohan, Chilukuri K., Grygiel, Jennifer, Zhou, Xinyi, Zafarani, Reza   +4 more
openaire   +2 more sources

Review of Fake News Detection on Social Media [PDF]

Jisuanji kexue
Fake news on social media not only jeopardizes cyberspace security,but also plays a pivotal role in major events,severely misleads the public and has a negative affect on political and social order.Therefore,this paper outlines social media fake news ...
CHEN Jing, ZHOU Gang, LI Shunhang, ZHENG Jiali, LU Jicang, HAO Yaohui
doaj   +1 more source

Fake news detection on social media: the predictive role of university students’ critical thinking dispositions and new media literacy

Smart Learning Environments, 2023
This study aimed to investigate the predictive role of critical thinking dispositions and new media literacies on the ability to detect fake news on social media. The sample group of the study consisted of 157 university students.
Ali Orhan
doaj   +1 more source

Unsupervised Fake News Detection [PDF]

Proceedings of the 31st ACM Conference on Hypertext and Social Media, 2020
Fake news has become more prevalent than ever, correlating with the rise of social media that allows every user to rapidly publish their views or hearsay. Today, fake news spans almost every realm of human activity, across diverse fields such as politics and healthcare.
Gangireddy, Siva Charan, Padmanabhan, Deepak, Long, Cheng, Chakraborty, Tanmoy   +3 more
openaire   +2 more sources

Fake Detect: A Deep Learning Ensemble Model for Fake News Detection [PDF]

Complexity, 2021
Pervasive usage and the development of social media networks have provided the platform for the fake news to spread fast among people. Fake news often misleads people and creates wrong society perceptions. The spread of low‐quality news in social media has negatively affected individuals and society.
Nida Aslam, Irfan Ullah Khan, Farah Salem Alotaibi, Lama Abdulaziz Aldaej, Asma Khaled Aldubaikil   +4 more
openaire   +2 more sources

A review of fake news detection approaches: A critical analysis of relevant studies and highlighting key challenges associated with the dataset, feature representation, and data fusion

Heliyon, 2023
Currently, social networks have become the main source to acquire news about current global affairs. However, fake news appears and spreads on social media daily.
Suhaib Kh Hamed, Mohd Juzaiddin Ab Aziz, Mohd Ridzwan Yaakub   +2 more
doaj   +1 more source

"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

, 2017
Automatic fake news detection is a challenging problem in deception detection, and it has tremendous real-world political and social impacts. However, statistical approaches to combating fake news has been dramatically limited by the lack of labeled ...
Wang, William Yang
core   +1 more source

Multimodal Fake News Detection

Information, 2022
Over the last few years, there has been an unprecedented proliferation of fake news. As a consequence, we are more susceptible to the pernicious impact that misinformation and disinformation spreading can have on different segments of our society. Thus, the development of tools for the automatic detection of fake news plays an important role in the ...
Isabel Segura-Bedmar, Santiago Alonso-Bartolome   +1 more
openaire   +4 more sources