How Consumers Consume Social Media Influence
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
A growing body of research has examined the efficacy of influencer marketing and how social media influencers (SMIs) produce influence through strategically manufacturing authenticity and relatability. Less clear, however, is what benefits consumers derive from influencers and how they incorporate influencer content into their own identity projects. In other words, advertisers and influencers do not know how consumers actually “consume” influence. The current research addresses this gap through developing a novel perspective on influencer marketing that highlights how consumers actively incorporate influencer content into their own practice performances. Based on a market ethnography of millennial and gen Z beauty consumers, this research uncovers six distinct actions through which consumers consume influence. Findings also challenge and update another core assumption of influencer marketing: that consumers generally perceive influencers to be similar to them. Altogether, this research introduces the Influencer Marketing Dartboard as a conceptual and managerial tool to better leverage influencers for marketing. Three contributions are offered that advance the influencer marketing and practice theory literatures: a deeper understanding of how companies can effectively utilize SMIs, a clearer differentiation between SMIs and celebrity endorsers, and insights into how mediated practices facilitate consumers’ identity projects.
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 | 0.001 | 0.011 |
| 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 | 0.001 |
| 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