Chinese Online Celebrities’ Discursive Strategies of Promoting Domestic Products: Online Posters as Multimodal Ensembles
Bibliographic record
Abstract
Although Chinese online celebrities have received much scholarly attention, scant studies pay attention to the crucial role they play in promoting the emerging “buy national” in China. This study investigates the multimodal discourse conveyed in a collection of advertising posters designed by online celebrities to promote Chinese domestic products (known as guohuo in China). Through a social semiotic lens, it provides a multimodal analysis of how online posters employ visual imaginary and textual messages for commercial purposes within the rising consumer nationalistic context. Drawing upon a dataset of 20 online posters, the analysis reveals a set of semiotic resources including color, image, typography, layout and non-linguistic gesture and gaze. These modes are employed collectively to orchestrate the national script and produce the authoritative representatives that convert the online posters into a kind of national multimodal ensemble. The study highlights the extensive spread of online posters and provides new insights for analyzing the visibility of online celebrities in the growing wave of “buy national” in China.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".