Analysis of the communication and composition of the digital press in Argentina, Peru, Mexico and Colombia in 2022
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 research was carried out with the aim of identifying the level of communication and structuring of the graphic patterns of publications on social networks Facebook, Instagram and Twitter. For this, four cases were chosen that are among the most influential newspapers in Latin America in the first quarter of 2022. These newspapers with greater influence are El Comercio Perú, El Universal, El Tiempo and La Nación considered so by the acceptance of their readers in print editions as in online. To collect the information, the inductive method was used by which topics such as typography, grids, interlettering, compositional elements, among others, were classified. And the method of analysis that serves to evaluate the behavior of the compositional elements individually of each publication. The focus of the research is mixed, since qualitative data were acquired: compositional and quantitative properties: interactions with more scope in the quarter of 2022. Along with this, the statistical data covered by eye tracking as an evaluation team in publications with greater scope or acceptance. In total there are 56 publications evaluated through the files and eleven with eye tracking. The data provided by the two evaluations contribute to the validation of the hypothesis in a theoretical and practical way. Concluding that the management of the structuring of graphic elements effectively affects acceptance in social media. The use of equipment related to neuromarketing is recommended. Which support the results obtainedthrough the application of theory in the designs.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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