Are Deep Learning-Generated Social Media Profiles Indistinguishable from Real Profiles?

Sippo Rossi, Youngjin Kwon, Odd Harald Auglend, Raghava Rao Mukkamala, Matti Rossi, Jason Bennett Thatcher

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Abstract

In recent years, deep learning methods have become increasingly capable of generating near photorealistic pictures and humanlike text up to the point that humans can no longer recognize what is real and what is AI-generated. Concerningly, there is evidence that some of these methods have already been adopted to produce fake social media profiles and content. We hypothesize that these advances have made detecting generated fake social media content in the feed extremely difficult, if not impossible, for the average user of social media. This paper presents the results of an experiment where 375 participants attempted to label real and generated profiles and posts in a simulated social media feed. The results support our hypothesis and suggest that even fully-generated fake profiles with posts written by an advanced text generator are difficult for humans to identify.
Original languageEnglish
Title of host publicationProceedings of the 56th Hawaii International Conference on System Sciences
EditorsTung X. Bui
Place of PublicationUnited States
PublisherHawaii International Conference on System Sciences
Pages134-143
Number of pages10
ISBN (Electronic)978-0-9981331-6-4
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventAnnual Hawaii International Conference on System Sciences - Maui, United States
Duration: 3 Jan 20236 Jan 2023
Conference number: 56

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605
ISSN (Electronic)2572-6862

Conference

ConferenceAnnual Hawaii International Conference on System Sciences
Abbreviated titleHICSS
Country/TerritoryUnited States
CityMaui
Period03/01/202306/01/2023

Keywords

  • Adversarial behavior in collaboration and social media systems
  • Deep learning
  • Experiment
  • GAN images
  • Social bots
  • Social media

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