Avatars as information: Perception of consumers based on their avatars in virtual worlds
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Insufficient payload (model declined to judge)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: Observational
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.230
- Threshold uncertainty score
- 0.993
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.301 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Abstract The presence of consumers and companies in the virtual worlds has increased in recent years. It is predicted that 80% of active Internet consumers and Fortune 500 companies will have an avatar or presence in a virtual community, including social networks, by the end of 2011 (eMarketer, 2007 ). The increase in the number of consumers with avatars emphasizes the need for a better understanding of who these consumers behind the avatars really are in order to convert these individuals to online and real‐world customers. The objective of this paper is to investigate how avatars reflect the personality of their creators (targets) in virtual worlds. Using the Brunswik Lens Model as the theoretical framework, an investigation of real consumers in the virtual world Second Life reveals that perceivers who view targets' avatar use particular thin‐slices of observations such as avatar cues (e.g., attractiveness, gender, hairstyle) to form accurate personality impressions about targets. The findings support the premise that real‐life companies that intend to expand to virtual worlds can use member avatars as a proxy for member personality and lifestyles. As a future research direction, avatars and other consumer‐generated media could be used as the basis for targeting and segmentation of online consumers. © 2010 Wiley Periodicals, Inc.
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.
The record
- Venue
- Psychology and Marketing
- Topic
- Evolutionary Psychology and Human Behavior
- Field
- Psychology
- Canadian institutions
- Concordia University
- Funders
- not available
- Keywords
- MetaverseAvatarAttractivenessPerceptionPsychologyPersonalityPremiseVirtuality (gaming)The InternetOrder (exchange)Proxy (statistics)AdvertisingVirtual worldSocial mediaVirtual realityHuman–computer interactionSocial psychologyInternet privacyComputer scienceWorld Wide WebBusinessArtificial intelligence
- Has abstract in OpenAlex
- yes