Three Fakes With Deep Learning Techniques Fake News, Fake Reviewers, and Deepfakes
| dc.contributor.author | Laor Boongasame | |
| dc.date.accessioned | 2026-05-08T19:24:14Z | |
| dc.date.issued | 2024-10-23 | |
| dc.description.abstract | The internet has brought convenience to the world. Many people communicate with each other through social media. Truth and lies are among the conveniences that people enjoy. Fake news and fake reviews cause problems for many people, both physically and mentally. For example, mentally, it may cause misunderstandings. Physically, it may lead to incorrect behavior towards the body, such as eating the wrong food or medicine. As a result, this paper presents a survey of research on various false stories that exist on social media. This paper will focus on three distinct topics: 1) fake news; 2) fake reviews; and 3) deepfakes. All three will be surveys of false stories used in deep learning. Some of the three tasks may contain the same information. At the same time, the theory may consist of multiple parts. Next, this chapter will present it in separate parts, hoping that readers will gain an understanding of fake social media and find it useful for future research. | |
| dc.identifier.doi | 10.4018/979-8-3693-7914-1.ch007 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/19486 | |
| dc.publisher | Advances in human and social aspects of technology book series | |
| dc.subject | Misinformation and Its Impacts | |
| dc.subject | Ethics and Social Impacts of AI | |
| dc.subject | Adversarial Robustness in Machine Learning | |
| dc.title | Three Fakes With Deep Learning Techniques Fake News, Fake Reviewers, and Deepfakes | |
| dc.type | Book-chapter |