Study on the Influence of Internet Celebrity Endorsements on Brand Marketing Strategies and Consumer Purchase Intention
Bibliographic record
Abstract
Live streaming has become a new way of communication and exchange between businesses and consumers, and internet celebrities have emerged in the context of live streaming. With their own traffic and amazing live streaming sales capabilities, internet celebrities have created new sales records one after another. Grassroots idols who have become popular through online platforms have considerable influence in their respective fields of expertise. Among them, microblog celebrities who have opened personal stores on Taobao have performed well in the economic model of flow realization. Due to the popularity of social media such as WeChat and Weibo on mobile devices, enterprise marketing emphasizes the importance of interacting with consumers, and content marketing has become the mainstream method of modern enterprise marketing. The research on the impact of internet celebrity marketing on clothing consumers' purchase intention has certain theoretical significance and practical value. Once a product is given the nickname of "internet celebrity", although its functional attributes remain the same but its presentation is different, it can still be highly praised and sales surge. Online celebrities frequently output distinctive content on social media to attract a large number of fans' attention and interact with them, ultimately achieving the goal of attracting traffic for their Taobao stores. This article takes internet celebrity brands as the research object and analyzes the influencing factors of internet celebrity endorsements on brand marketing and consumer purchase intention.
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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 | 0.002 | 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 | 0.000 |
| 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 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".