Research on the Development prospects of China's Internet celebrity market and Internet celebrity economy: Digital field survey based on social media
Bibliographic record
Abstract
At present, as an influential group in the Internet space, it is of particular Research significance to discuss the value of the Internet celebrity economy. This study examines how Internet celebrities can attract fans to generate traffic and monetize it through short videos and live broadcasts on social media, utilizing field surveys and questionnaire surveys. It reveals that promoting the marketing of influencers also brings many shortcomings. For example, some Internet celebrities use their fame to conceal public situations and highlight their own fame. The key to maintaining the competitiveness of Internet celebrities is to support and produce. This study outlines the essence of the Internet celebrity economy and influencer marketing. It points out that its core lies in the branding of Internet celebrity status, which can win fans' love with the help of multi-faceted support. At the same time, this article believes that influencer marketing is a crucial means of communication for Internet celebrities. The trust and interaction between Internet celebrities and fans strengthen brand identity and consumption transformation, showing the deep integration of media communication and consumer culture. Based on the theory of quasi-social interaction.
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How this classification was reachedexpand
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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".