Bibliographic record
Abstract
In Internet marketing, organizations leverage the Internet and related technologies to promote themselves, their products, their services, and their brands. In virtually all sectors, recent advances in Web technologies have dramatically changed the nature and volume of Internet marketing. Competition in online advertising is currently very intense as organizations have shifted their focus from print and other traditional advertising media to emails, search engines, and social media outlets for most of their promotional activities. However, due to the growing convergence of digital technologies, distinguishing one form of online marketing from another is becoming increasingly difficult. The current practice shows that there is a significant overlap of technologies as well as activities in most of the online marketing and advertising outlets. This chapter attempts to provide a classification of the major forms of Internet marketing (or online advertising) available, and discuss the key technological trends, practices, and academic research in each area. In particular, the chapter highlights the changing trends in Internet marketing due to recent developments in Web 2.0 and social media technologies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.150 | 0.072 |
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".