ANALISIS ISI PADA KOLOM KOMENTAR YOUTUBE MUSIK VIDEO ZIVA MAGNOLYA YANG BERJUDUL CUKUP
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
The comment column on platforms such as YouTube creates an MV space as a medium of communication where viewers can actively participate. This content analysis includes discussions, praise, criticism, and sharing personal stories related to the song. Music video. Want to know how netizens respond to the Music Video "Ziva Magnolya - Cukup. To find out how netizens respond to the Music Video "Ziva Magnolya - Cukup, the research used in this study is a descriptive qualitative approach. In this study, content analysis was used. The time of data collection in this study was November 24, 2023. The comment data used was obtained using the scraping technique from the "Google Apps Script" website. dominant group who are proud of the song entitled "cukup" sung by Ziva Magnolya. Netizens in this category show their admiration for the character, lyrics, music quality, and the way Ziva Magnolya performs the song which ultimately makes the listeners feel as if they are drowning and feel a very deep feeling for the song sung by Ziva Magnolya entitled cukup. Research on Ziva Magnolya's music video entitled "Cukup" on the YouTube platform found various responses from the audience. However, most netizens gave comments that they liked the lyrics of the song and liked Ziva Magnolya. Netizens also gave comments that showed emotional levels in the form of happiness and enthusiasm after hearing Ziva Magnolya's song entitled "Cukup" through the Youtube account.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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