Speech Act Analysis of Whatsapp Statuses Used by Jordanians
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
This qualitative study aims at investigating the WhatsApp statuses as used by Jordanians. It also investigates the types of speech acts used in these statuses. For this purpose, the study has collected and analyzed 200 statuses. The population of the study included all English language students of Jadadra University, where the sample of the study included (50) students, representing 20 % of the whole population. The results showed that data were classified into six main topics; religious, social, political, personal, romantic and national. Additionally, five themes emerged from the data, namely, expressive, directive, assertive, commissive and declaration. Expressive speech acts represent (37 %) of the total speech acts types analyzed. The directive took the second place, representing (25%) of the total status update analyzed. The assertive and commisive fall into the third and fourth position representing (23%) and (15%) respectively. The declarative type has the no occurrences representing (0 %) of the analyzed data. Some of the recommendations suggested are that further research needs to be conducted into the speech acts used by Jordanians on different social networking platforms.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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