Política 2.0 - Um estudo da utilização das redes sociais na pré-campanha presidencial brasileira de 2014
Bibliographic record
Abstract
The study was developed in order to analyze qualitatively and quantitatively the use of social networks for pre-candidates for the presidency of Brazil. Analyzes of all posts in the analyzed profiles of the two largest social networks in number of users in Brazil, Facebook and Twitter, during the first quarter of the election year 2014 were made. Besides the three main pre-presidential candidates, Dilma Rousseff, Eduardo Neves Campos and Aecio Neves, the main subjects classified as forming opinions of pre-candidates, such as Lula and Marina Silva were analyzed. All postings were analyzed for their content and the topic discussed, along with the level of interaction with the users of the networks, either through comments, shares and likes. For this study a questionnaire with professionals who have contributed together with the theory scholars have to define what would be a good use of social networks and a questionnaire in which the professionals evaluated the profiles of the individuals studied by BCEI model was also performed.
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.
How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".