Impact of Deepfake Technology on Social Media: Detection, Misinformation and Societal Implications

The rise of Artificial Intelligence (AI) has opened up new possibilities, but it also brings significant challenges. Deepfake technology, which creates realistic fake videos, raises concerns about privacy, identity, and consent. This paper explores the impacts of deepfakes and suggests solutions to mitigate their negative effects. Deepfake technology, which allows the manipulation and fabrication of audio, video, and images, has gained significant attention due to its potential to deceive and manipulate. As deepfakes proliferate on social media platforms, understanding their impact becomes crucial. This research investigates the detection, misinformation, and societal implications of deepfake technology on social media. Through a comprehensive literature review, the study examines the development and capabilities of deepfakes, existing detection techniques, and challenges in identifying them. The role of deepfakes in spreading misinformation and disinformation is explored, highlighting their potential consequences on public trust and social cohesion. The societal implications and ethical considerations surrounding deepfakes are examined, along with legal and policy responses. Mitigation strategies, including technological advancements and platform policies, are discussed. By shedding light on these critical aspects, this research aims to contribute to a better understanding of the impact of deepfake technology on social media and to inform future efforts in detection, prevention, and policy development. Keywords: Deepfake, Social media, Artificial intelligence, Generative adversarial networks, Deep neural networks.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-31
DOI
https://doi.org/10.22214/ijraset.2025.67997
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Impact of Deepfake Technology on Social Media: Detection, Misinformation and Societal Implications

Love Ghariwala
International Journal for Research in Applied Science and Engineering Technology
Spam and Phishing Detection
article

Impact of Deepfake Technology on Social Media: Detection, Misinformation and Societal Implications

Love Ghariwala
article en

Abstract

The rise of Artificial Intelligence (AI) has opened up new possibilities, but it also brings significant challenges. Deepfake technology, which creates realistic fake videos, raises concerns about privacy, identity, and consent. This paper explores the impacts of deepfakes and suggests solutions to mitigate their negative effects. Deepfake technology, which allows the manipulation and fabrication of audio, video, and images, has gained significant attention due to its potential to deceive and manipulate. As deepfakes proliferate on social media platforms, understanding their impact becomes crucial. This research investigates the detection, misinformation, and societal implications of deepfake technology on social media. Through a comprehensive literature review, the study examines the development and capabilities of deepfakes, existing detection techniques, and challenges in identifying them. The role of deepfakes in spreading misinformation and disinformation is explored, highlighting their potential consequences on public trust and social cohesion. The societal implications and ethical considerations surrounding deepfakes are examined, along with legal and policy responses. Mitigation strategies, including technological advancements and platform policies, are discussed. By shedding light on these critical aspects, this research aims to contribute to a better understanding of the impact of deepfake technology on social media and to inform future efforts in detection, prevention, and policy development. Keywords: Deepfake, Social media, Artificial intelligence, Generative adversarial networks, Deep neural networks.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Openalex Percentile: Top 93%
Spam and Phishing Detection
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