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AIP Conference Proceedings, 2023 Everyone nowadays gets their news from a variety of online sources in the age of the internet. The news quickly reached millions of users thanks to the increasing use of social media platforms like Facebook and Twitter. The most prevalent form of unverified and false information is rumors and fake news, both of which should be flagged as soon as ...
Vinya Shree Nadipelli +2 more
+5 more sources
Fake news detection: A survey of graph neural network methods [PDF]
Applied Soft Computing Journal, 2023 Huyen Trang Phan +2 more
exaly +2 more sources
Fake News Detection on Social Networks: A Survey
Applied Sciences, 2023 In recent years, social networks have developed rapidly and have become the main platform for the release and dissemination of fake news. The research on fake news detection has attracted extensive attention in the field of computer science.
Yanping Shen +4 more
doaj +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 +1 more
openaire +4 more sources
Topic-Aware Fake News Detection Based on Heterogeneous Graph
IEEE Access, 2023 In recent years, fake news has had a bad impact on individuals and society, which has aroused widespread concern about fake news detection. The existing heterogeneous graph-based fake news detection model (CompareNet) mainly focuses on the semantic ...
Lijuan Sun, Hongbin Wang
doaj +1 more source
Utilization Strategy of User Engagements in Korean Fake News Detection
IEEE Access, 2022 Fake News (disinformation with malicious intent) has emerged as a major social problem. To address this issue, previous studies mainly utilized single information, the news content, to detect fake news.
Myunghoon Kang +3 more
doaj +1 more source
Systems, 2023 With the popularization of digital technology, the problem of information pollution caused by fake news has become more common. Malicious dissemination of harmful, offensive or illegal content may lead to misleading, misunderstanding and social unrest ...
Lu Yuan +4 more
doaj +1 more source
IEEE Access, 2023 As fake news spreads rapidly in social media, attempts to develop detection technology to automatically identify fake news are actively being developed, recently.
Minjung Park, Sangmi Chai
doaj +1 more source
A Comprehensive Review on Fake News Detection With Deep Learning
IEEE Access, 2021 A protuberant issue of the present time is that, organizations from different domains are struggling to obtain effective solutions for detecting online-based fake news.
M. F. Mridha +4 more
doaj +1 more source
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.
Niraj Sitaula +4 more
openaire +2 more sources