Deepfake Technology: A Comprehensive Analysis of its Societal Implications and Impact (in-depth interview with experts)

Ahmed, S., Ng, S. W. T., & Bee, A. W. T. (2023). Understanding the role of fear of missing out and deficient self-regulation in sharing of deepfakes on social media: Evidence from eight countries. *Frontiers in Psychology.

URL:https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1127507/full

 Ahmed, S., Sonuç, E., Ahmed Ahmed, M. R., & Duru, A. (2022). Analysis Survey on Deepfake detection and Recognition with Convolutional Neural Networks. *2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). URL: https://ieeexplore.ieee.org/document/9799858

Ali, A., Ghouri, K. F. K., Naseem, H., Soomro, T. R., Mansoor, W., & Momani, A. M. (2022). Battle of Deep Fakes: Artificial Intelligence Set to Become a Major Threat to the Individual and National Security. In 2022 International Conference on Cyber Resilience (ICCR)* (pp. 1-5).URL: https://ieeexplore.ieee.org/document/9995821

Amezaga, N., & Hajek, J. (2022). Availability of Voice Deepfake Technology and its Impact for Good and Evil. Proceedings of the 23rd Annual Conference on Information Technology Education.URL: https://dl.acm.org/doi/10.1145/3537674.3554742

Buo, S. A. (2020). The Emerging Threats of Deepfake Attacks and Countermeasures. ArXiv.URL: https://www.researchgate.net/publication/347096267_The_Emerging_Threats_of_Deepfake_Attacks_and_Countermeasures?channel=doi&linkId=5fd7e57a45851553a0ba01ed&showFulltext=true

Das, R., Negi, G., & Smeaton, A. (2021). Detecting Deepfake Videos Using Euler Video Magnification. ArXiv.URL: https://library.imaging.org/ei/articles/33/4/art00003

de Ruiter, A. (2021). The Distinct Wrong of Deepfakes. *Philosophy & Technology, 34*, 1311-1332.URL: https://link.springer.com/article/10.1007/s13347-021-00459-2

de Seta, G. (2021). Huanlian, or changing faces: Deepfakes on Chinese digital media platforms. *Convergence: The International Journal of Research into New Media Technologies, 27, 935–953. URL: https://journals.sagepub.com/doi/10.1177/13548565211030185

 Diakopoulos, N., & Johnson, D. G. (2020). Anticipating and addressing the ethical implications of deepfakes in the context of elections. New Media & Society, 23, 2072-2098. URL: https://journals.sagepub.com/doi/10.1177/1461444820925811

Dobrobaba, M. (2022). Deepfakes as a Threat to Human Rights. Lex Russica. URL: https://lexrussica.msal.ru/jour/article/view/2728

Emerald Expert Briefings. (2019). 'Deepfakes' could irreparably damage public trust. URL: https://www.emerald.com/insight/content/doi/10.1108/OXAN-DB247351/full/html

Fletcher, J. (2019). Deepfakes, Artificial Intelligence, and Some Kind of Dystopia: The New Faces of Online Post-Fact Performance. Theatre Journal, 70, 455-471. URL: https://muse.jhu.edu/article/715916

Frolov, D. B., Makhaev, D. D., & Shishkarev, V. V. (2022). Deepfakes and Information Security Issues. *2022 International Conference on Quality Management, Transport and Information Security, Information Technologies (IT&QM&IS), 147-150. URL: https://ieeexplore.ieee.org/document/9976507/

Geddes, K. (2020). Ocularcentrism and Deepfakes: Should Seeing Be Believing? Social ScienceResearchNetwork.URL:https://ir.lawnet.fordham.edu/cgi/viewcontent.cgi?article=1781&context=iplj

Godulla, A., Hoffmann, C., & Seibert, D. (2021). Dealing with deepfakes – an interdisciplinary examination of the state of research and implications for communication studies. Studies in Communication and Media. URL: https://www.nomos-elibrary.de/10.5771/2192-4007-2021-1-72/dealing-with-deepfakes-an-interdisciplinary-examination-of-the-state-of-research-and-implications-for-communication-studies-jahrgang-10-2021-heft-1?page=1

Hancock, J., & Bailenson, J. (2021). The Social Impact of Deepfakes. *Cyberpsychology, Behavior, and Social Networking, 24(3), 149–152.

 URL: https://www.liebertpub.com/doi/10.1089/cyber.2021.29208.jth

Hanif, S. M., & Dave, V. (2022). Deepfakes Technology Using AI. *International Journal of Scientific Research in Science, Engineering and Technology.

URL: https://ijsrset.com/IJSRSET229522

Hight, C. (2021). Deepfakes and documentary practice in an age of misinformation. Continuum, 36, 393-410.

URL: https://www.tandfonline.com/doi/full/10.1080/10304312.2021.2003756

Hughes, S., Fried, O., Ferguson, M., Hughes, C., Hughes, R., Yao, D., & Hussey, I. (2021). Deepfaked online content is highly effective in manipulating people’s attitudes and intentions. URL: https://osf.io/4ms5a

Ivanov, V. G., & Ignatovskiy, Y. R. (2020). Deepfakes: Prospects for Political Use and Threats to the Individual and National Security. RUDN Journal of Public Administration. URL: https://journals.rudn.ru/public-administration/article/view/24985

Jalui, K., Jagtap, A., Sharma, S., Mary, G., Fernandes, R., & Kolhekar, M. M. (2022). Synthetic Content Detection in Deepfake Video using Deep Learning. 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT), 1-5.

URL: https://ieeexplore.ieee.org/document/9972081

Judge, E. F., & Korhani, A. M. (2021). Deepfakes, Counterfeits, and Personality. SSRN Electronic Journal.URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3893890

Khatri, N., Borar, V., & Garg, R. (2023). A Comparative Study: Deepfake Detection Using Deep-learning. 2023 13th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 1-5. URL: https://ieeexplore.ieee.org/document/10048888

Khichi, M., & Yadav, R. (2021). A Threat of Deepfakes as a Weapon on Digital Platform and their Detection Methods. 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 01-08.

 URL: https://ieeexplore.ieee.org/document/9580031/

Kietzmann, J. H., Lee, L. W., McCarthy, I. P., & Kietzmann, T. C. (2020). Deepfakes: Trick or treat? Business Horizons, 63(1), 135–146.

URL: https://www.sciencedirect.com/science/article/abs/pii/S0007681319301600?via%3Dihub

Kwok, A. O. J., & Koh, S. G. M. (2020). Deepfake: a social construction of technology perspective. Current Issues in Tourism, 24, 1798–1802.

URL: https://www.tandfonline.com/doi/full/10.1080/13683500.2020.1738357

Langer, M., & Wyczik, J. (2020). Legal Aspects of Deepfakes. Roczniki Administracji i Prawa

.URL:https://rocznikiadministracjiiprawa.publisherspanel.com/resources/html/article/details?id=215207&language=en

Laser, C. J., & Goldman, E. (2021). Deepfakes, Privacy, and Freedom of Speech. SSRN Electronic Journal.URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3869850

Latané, B. (1996). Dynamic Social Impact: The Creation of Culture by Communication. Journal of Communication, 46, 13–25.

URL: https://academic.oup.com/joc/article-abstract/46/4/13/4160264?redirectedFrom=fulltext

Le, B. M., Tariq, S., Abuadbba, A., Moore, K., & Woo, S. S. (2023). Why Do Deepfake Detectors Fail? ArXiv, abs/2302.13156. URL: https://arxiv.org/abs/2302.13156

Lin, K., Han, W., Gu, Z., & Li, S. (2021). A Survey of DeepFakes Generation and Detection. 2021 IEEE Sixth International Conference on Data Science in Cyberspace (DSC), 474-478.URL: https://ieeexplore.ieee.org/document/9750440/

Masood, M., Nawaz, M., Malik, K. M., Javed, A., & Irtaza, A. (2021). Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forward. ArXiv, abs/2103.00484. URL: https://link.springer.com/article/10.1007/s10489-022-03766-z

Mirsky, Y., & Lee, W. (2020). The Creation and Detection of Deepfakes. ACM Computing Surveys (CSUR), 54, 1-41.URL: https://dl.acm.org/doi/10.1145/3425780

Mitra, A., Mohanty, S., Corcoran, P., & Kougianos, E. (2021). A Machine Learning Based Approach for Deepfake Detection in Social Media Through Key Video Frame Extraction. SN Computer Science, 2. URL: https://link.springer.com/article/10.1007/s42979-021-00495-x

Nettle, D. (1999). Using Social Impact Theory to simulate language change. Lingua, 108, 95-117.URL: https://linkinghub.elsevier.com/retrieve/pii/S0024384198000461

Nguyen, T. T., Nguyen, C. M., Nguyen, D. T., Nguyen, D. T., & Nahavandi, S. (2019). Deep Learning for Deepfakes Creation and Detection. ArXiv.

URL: https://export.arxiv.org/pdf/1909.11573

P, S., & Sk, S. (2021). DeepFake Creation and Detection: A Survey. *2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA),584-588.URL: https://ieeexplore.ieee.org/document/9544522

Pan, D., Sun, L., Wang, R., Zhang, X., & Sinnott, R. (2020). Deepfake Detection through Deep Learning. 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT).URL: https://ieeexplore.ieee.org/document/9302547

Patil, K., Kale, S., Dhokey, J., & Gulhane, A. A. (2023). Deepfake Detection using Biological Features: A Survey. ArXiv, abs/2301.05819*. URL: https://arxiv.org/abs/2301.05819

Schroeder, J. (2019). Free Expression Rationales and the Problem of Deepfakes Within the E.U. and U.S. Legal Systems. SSRN Electronic Journal.

 URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3503617

Shad, H. S., Rizvee, M. M., Roza, N. T., Hoq, S. M. A., Khan, M. M., Singh, A., Zaguia, A., & Bourouis, S. (2021). Comparative Analysis of Deepfake Image Detection Method Using Convolutional Neural Network. Computational Intelligence and Neuroscience, 2021.URL:https://www.researchgate.net/publication/357123371_Comparative_Analysis_of_Deepfake_Image_Detection_Method_Using_Convolutional_Neural_Network

Singh, R., Sarda, P. V., Aggarwal, S., & Vishwakarma, D. (2021). Demystifying deepfakes using deep learning. 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), 1290-1298.

URL: https://ieeexplore.ieee.org/document/9418477/

1909. Nguyen, C. Nguyen, Dung Nguyen, D. Nguyen, & Nahavandi, S. (2019). Deep Learning for Deepfakes Creation and Detection. ArXiv. URL: https://export.arxiv.org/pdf/1909.11573

Vaccari, C., & Chadwick, A. (2020). Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News. Social Media + Society, 6.URL: https://journals.sagepub.com/doi/10.1177/2056305120903408

Vasist, P. N., & Krishnan, S. (2022). Engaging with deepfakes: a meta-synthesis from the perspective of social shaping of technology theory. Internet Research. URL: https://www.emerald.com/insight/content/doi/10.1108/INTR-06-2022-0465/full/html

Vatreš, A. (2021). Deepfake Phenomenon: An Advanced Form of Fake News and Its Implications on Reliable Journalism. Društvene i humanističke studije (Online). URL: http://www.dhs.ff.untz.ba/index.php/home/article/view/574

Verdoliva, L. (2022). Deepfake Detection: State-of-the-art and Future Directions. Proceedings of the 1st Workshop on Security Implications of Deepfakes and Cheapfakes. URL: https://dl.acm.org/doi/10.1145/3494109.3527197

Vizoso, Á., Vaz-Álvarez, M., & López-García, X. (2021). Fighting Deepfakes: Media and Internet Giants’ Converging and Diverging Strategies Against Hi-Tech Misinformation. Media and Communication, 9, 291-300.

URL: https://www.cogitatiopress.com/mediaandcommunication/article/view/3494

Whittaker, L., Letheren, K., & Mulcahy, R. (2021). The Rise of Deepfakes: A Conceptual Framework and Research Agenda for Marketing. Australasian Marketing Journal, 29(2), 204-214.URL: https://journals.sagepub.com/doi/10.1177/1839334921999479

Zhou, X., Wang, Y., & Wu, P. (2020). Detecting Deepfake Videos via Frame Serialization Learning. 2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI), 391-395.URL: https://ieeexplore.ieee.org/document/9332419/

Zi, B., Chang, M., Chen, J., Ma, X., & Jiang, Y.-G. (2020). WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection. In Proceedings of the 28th ACM International Conference on Multimedia.URL: https://dl.acm.org/doi/10.1145/3394171.3413769