E-Marketing via Social Networking and Its Role on the Enhancement of Small Business Projects
Bibliographic record
Abstract
This study aimed to highlight the concepts of e-marketing through social networking sites and its role in the enhancement of small business projects; and the extent to which it is effective for proprietors of such projects. Questionnaire technique was used for collecting data from large number of individuals. Analysis of data was performed by using the analytic and descriptive approaches. The population was comprised of some directors of the small business projects in the Kingdom of Saudi Arabia. The study evaluated that there is a general recognition for the significance of using social networking sites in marketing. To advertise the products and services of the small business projects in consideration with social media sites as a modern method for e-marketing together with its widespread application, it is essential to utilize the need for taking advantage from the revolution of social networking sites in marketing sector. Doing so will give attention to creative activities related to the sorts of such small projects, and attempt to know continuously the latest electronic applications. The retrieved outcomes of the study demonstrate that how e-marketing and social networking sites support small business projects and identify the major obstacles faced by the proprietors in Saudi Arabia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".