From desire to help to taking action: Effects of personal traits and social media on market mavens’ diffusion of information
Bibliographic record
Abstract
Abstract While extant research has studied traits of market mavens and the link from mavenism to market helping behavior, there is a need for more research to understand personal and contextual factors that influence actual recommendations of products and differences among market mavens with different traits in that respect. In this study, we took research in the area of market mavenism one step further and investigated the role of personal traits such as self‐esteem and susceptibility to normative interpersonal influence, and the contextual factor of social media, in the frequency of recommendations. We hypothesize that while market mavens with lower self‐esteem are likely to engage in less frequent recommendations, negative effect of their lower self‐esteem is attenuated when they use social media platforms as their medium of choice. Our findings lend support to our hypotheses, including the triple interaction effect between self‐esteem, choice of social media, and market mavenism on market recommendations.
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.
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 | 0.001 | 0.003 |
| 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".