Guo Freeman

Keyan Guo, Ayush Utkarsh, Wenbo Ding et al.

Online user generated content games (UGCGs) are increasingly popular among children and adolescents for social interaction and more creative online entertainment. However, they pose a heightened risk of exposure to explicit content, raising growing concerns for the online safety of children and adolescents. Despite these concerns, few studies have addressed the issue of illicit image-based promotions of unsafe UGCGs on social media, which can inadvertently attract young users. This challenge arises from the difficulty of obtaining comprehensive training data for UGCG images and the unique nature of these images, which differ from traditional unsafe content. In this work, we take the first step towards studying the threat of illicit promotions of unsafe UGCGs. We collect a real-world dataset comprising 2,924 images that display diverse sexually explicit and violent content used to promote UGCGs by their game creators. Our in-depth studies reveal a new understanding of this problem and the urgent need for automatically flagging illicit UGCG promotions. We additionally create a cutting-edge system, UGCG-Guard, designed to aid social media platforms in effectively identifying images used for illicit UGCG promotions. This system leverages recently introduced large vision-language models (VLMs) and employs a novel conditional prompting strategy for zero-shot domain adaptation, along with chain-of-thought (CoT) reasoning for contextual identification. UGCG-Guard achieves outstanding results, with an accuracy rate of 94% in detecting these images used for the illicit promotion of such games in real-world scenarios.

Divine Maloney, Guo Freeman, Andrew Robb

The boom of commercial social virtual reality (VR) platforms in recent years has signaled the growth and wide-spread adoption of consumer VR. Social VR platforms draw aspects from traditional 2D virtual worlds where users engage in various immersive experiences, interactive activities, and choices in avatar-based representation. However, social VR also demonstrates specific nuances that extend traditional 2D virtual worlds and other online social spaces, such as full/partial body tracked avatars, experiencing mundane everyday activities in a new way (e.g., sleeping), and an immersive means to explore new and complex identities. The growing popularity has signaled interest and investment from top technology companies who each have their own social VR platforms. Thus far, social VR has become an emerging research space, mainly focusing on design strategies, communication and interaction modalities, nuanced activities, self-presentation, harassment, privacy, and self-disclosure. These recent works suggest that many questions still remain in social VR scholarship regarding how to ethically conduct research on these sites and which research areas require additional attention. Therefore, in this paper, we provide an overview of modern Social VR, critically review current scholarship in the area, raise ethical considerations for conducting research on these sites, and highlight unexplored areas.