Investigating VTubing as a Reconstruction of Streamer Self-Presentation:
Identity, Performance, and Gender
- URL: http://arxiv.org/abs/2307.11025v2
- Date: Thu, 29 Feb 2024 15:43:09 GMT
- Title: Investigating VTubing as a Reconstruction of Streamer Self-Presentation:
Identity, Performance, and Gender
- Authors: Qian Wan and Zhicong Lu
- Abstract summary: VTubers are live streamers who create streaming content using animated 2D or 3D virtual avatars.
This research explores how this flexibility influences how creators present themselves.
The socio-technical facets of VTubing were found to potentially reduce sexual harassment and sexism, whilst also raising self-objectification concerns.
- Score: 24.535792750960713
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: VTubers, or Virtual YouTubers, are live streamers who create streaming
content using animated 2D or 3D virtual avatars. In recent years, there has
been a significant increase in the number of VTuber creators and viewers across
the globe. This practise has drawn research attention into topics such as
viewers' engagement behaviors and perceptions, however, as animated avatars
offer more identity and performance flexibility than traditional live streaming
where one uses their own body, little research has focused on how this
flexibility influences how creators present themselves. This research thus
seeks to fill this gap by presenting results from a qualitative study of 16
Chinese-speaking VTubers' streaming practices. The data revealed that the
virtual avatars that were used while live streaming afforded creators
opportunities to present themselves using inflated presentations and resulted
in inclusive interactions with viewers. The results also unveiled the inflated,
and often sexualized, gender expressions of VTubers while they were situated in
misogynistic environments. The socio-technical facets of VTubing were found to
potentially reduce sexual harassment and sexism, whilst also raising
self-objectification concerns.
Related papers
- AnimeGamer: Infinite Anime Life Simulation with Next Game State Prediction [58.240114139186275]
Recently, a pioneering approach for infinite anime life simulation employs large language models (LLMs) to translate multi-turn text dialogues into language instructions for image generation.
We propose AnimeGamer, which is built upon Multimodal Large Language Models (MLLMs) to generate each game state.
We introduce novel action-aware multimodal representations to represent animation shots, which can be decoded into high-quality video clips.
arXiv Detail & Related papers (2025-04-01T17:57:18Z) - Vid2Avatar-Pro: Authentic Avatar from Videos in the Wild via Universal Prior [31.780579293685797]
We present Vid2Avatar-Pro, a method to create photorealistic and animatable 3D human avatars from monocular in-the-wild videos.
arXiv Detail & Related papers (2025-03-03T14:45:35Z) - Virtual Stars, Real Fans: Understanding the VTuber Ecosystem [8.461062537658846]
We conduct a comprehensive analysis of VTuber viewers on Bilibili, a leading livestreaming platform where nearly all VTubers in China stream.
By compiling a first-of-its-kind dataset covering 2.7M livestreaming sessions, we investigate the characteristics, engagement patterns, and influence of VTuber viewers.
We leverage to develop a tool to "recommend" future subscribers to VTubers.
arXiv Detail & Related papers (2025-02-03T17:33:54Z) - EgoAvatar: Egocentric View-Driven and Photorealistic Full-body Avatars [56.56236652774294]
We propose a person-specific egocentric telepresence approach, which jointly models the photoreal digital avatar while also driving it from a single egocentric video.
Our experiments demonstrate a clear step towards egocentric and photoreal telepresence as our method outperforms baselines as well as competing methods.
arXiv Detail & Related papers (2024-09-22T22:50:27Z) - Bring Your Own Character: A Holistic Solution for Automatic Facial
Animation Generation of Customized Characters [24.615066741391125]
We propose a holistic solution to automatically animate virtual human faces.
A deep learning model was first trained to retarget the facial expression from input face images to virtual human faces.
A practical toolkit was developed using Unity 3D, making it compatible with the most popular VR applications.
arXiv Detail & Related papers (2024-02-21T11:35:20Z) - GAIA: Zero-shot Talking Avatar Generation [64.78978434650416]
We introduce GAIA (Generative AI for Avatar), which eliminates the domain priors in talking avatar generation.
GAIA beats previous baseline models in terms of naturalness, diversity, lip-sync quality, and visual quality.
It is general and enables different applications like controllable talking avatar generation and text-instructed avatar generation.
arXiv Detail & Related papers (2023-11-26T08:04:43Z) - It is not Sexually Suggestive, It is Educative. Separating Sex Education
from Suggestive Content on TikTok Videos [22.870334358353585]
SexTok is a dataset composed of TikTok videos labeled as sexually suggestive (from the annotator's point of view), sex-educational content, or neither.
Children's exposure to sexually suggestive videos has been shown to have adversarial effects on their development.
Virtual sex education, especially on subjects that are more relevant to the LGBTQIA+ community, is very valuable.
arXiv Detail & Related papers (2023-07-06T20:23:17Z) - How Would The Viewer Feel? Estimating Wellbeing From Video Scenarios [73.24092762346095]
We introduce two large-scale datasets with over 60,000 videos annotated for emotional response and subjective wellbeing.
The Video Cognitive Empathy dataset contains annotations for distributions of fine-grained emotional responses, allowing models to gain a detailed understanding of affective states.
The Video to Valence dataset contains annotations of relative pleasantness between videos, which enables predicting a continuous spectrum of wellbeing.
arXiv Detail & Related papers (2022-10-18T17:58:25Z) - Can gender categorization influence the perception of animated virtual
humans? [0.0]
We reproduce, through CG, a perceptual study that aims to assess gender bias in relation to a simulated baby.
The results of our study with virtual babies were similar to the findings with real babies.
arXiv Detail & Related papers (2022-08-03T23:45:49Z) - "Nudes? Shouldn't I charge for these?" : Motivations of New Sexual
Content Creators on OnlyFans [5.829936645872441]
OnlyFans creators are uniquely positioned at the intersection of professional social media content creation and sex work.
Our participants were motivated by three key factors: (1) societal visibility and mainstream acceptance of OnlyFans; (2) platform design and affordances such as boundary setting with clients, privacy from the public, and content archives; and (3) the pandemic.
arXiv Detail & Related papers (2022-05-20T19:59:51Z) - Subjective and Objective Analysis of Streamed Gaming Videos [60.32100758447269]
We study subjective and objective Video Quality Assessment (VQA) models on gaming videos.
We created a novel gaming video video resource, called the LIVE-YouTube Gaming video quality (LIVE-YT-Gaming) database, comprised of 600 real gaming videos.
We conducted a subjective human study on this data, yielding 18,600 human quality ratings recorded by 61 human subjects.
arXiv Detail & Related papers (2022-03-24T03:02:57Z) - Audio- and Gaze-driven Facial Animation of Codec Avatars [149.0094713268313]
We describe the first approach to animate Codec Avatars in real-time using audio and/or eye tracking.
Our goal is to display expressive conversations between individuals that exhibit important social signals.
arXiv Detail & Related papers (2020-08-11T22:28:48Z) - #MeToo on Campus: Studying College Sexual Assault at Scale Using Data
Reported on Social Media [71.74529365205053]
We analyze the influence of the # trend on a pool of college followers.
The results show that the majority of topics embedded in those # tweets detail sexual harassment stories.
There exists a significant correlation between the prevalence of this trend and official reports on several major geographical regions.
arXiv Detail & Related papers (2020-01-16T18:05:46Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.