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
In this paper, we identify emotion as an essential element of interaction between members of a brand community in a social networking site. Emotions play an important role in the interaction, since they create narratives through speech, vocabulary, images, symbols, rituals, etc. [28, 26]. Through a mixed method approach, heavily based on a content analysis, we highlighted the emotional elements used for interaction within a brand community. In order to achieve our goals, we analyzed 77 posts and 13,043 comments from members of the brand community "Starbucks Mexico" on Facebook, reported between January and June 2014. The contribution that we present here includes the detection of positive and negative emotions expressed on Facebook, as well as the level of participation that they generate, and the distinction of elements used to express emotions. We found that people interact more through emotions related to happiness, such as love, passion, and desire. But also, negative emotions like anger and longing are often used to generate participation.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.002 |
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