Social networking sites as a learning tool
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
Purpose – Over the past few years, social networking sites (SNSs) have become very useful for firms, allowing companies to manage the customer–brand relationships. In this context, SNSs can be considered as a learning tool because of the brand knowledge that customers develop from these relationships. Because of the fact that knowledge in organisations is embodied in the concept of the learning organisation, customers may create brand knowledge as a consequence of two learning facilitators: informational and instrumental value. Then, the purpose of this paper is to identify the role played by brand knowledge in the process of creating customer capital, in the context of SNSs. Design/methodology/approach – A total of 259 users of SNSs, who were followers or fans of brand pages, participated in this study. Data were collected through an online survey and they were analysed using structural equation modelling. Findings – The results of the study show that brand pages at SNS can perform brand knowledge by providing purposive gratifications to its customers. Moreover, they can also develop an indirect effect on customer capital, through the direct effect that brand knowledge has on it. Therefore, the results of the study will help managers design their learning strategies in relation to SNS and confirm the need of using SNS as a learning tool. Originality/value – Few, if any, studies have analysed whether gratifications, usually related to media, work as learning facilitators in the context of brand pages at SNS.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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 it