More Kawaii than a Real-Person Live Streamer: Understanding How the Otaku Community Engages with and Perceives Virtual YouTubers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership in East Asia. Although prior research has found that many viewers seek real-life interpersonal interactions with real-person streamers, it is currently unknown what makes VTuber live streams engaging or how they are perceived differently than real-person streamers. We conducted an interview study to understand how viewers engage with VTubers and perceive the identities of the voice actors behind the avatars (i.e., Nakanohito). The data revealed that Virtual avatars bring unique performative opportunities which result in different viewer expectations and interpretations of VTuber behavior. Viewers intentionally upheld the disembodiment of VTuber avatars from their voice actors. We uncover the nuances in viewer perceptions and attitudes and further discuss the implications of VTuber practices to the understanding of live streaming in general.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it