Analisis Video Comments to Followers Ratio Instagram Pada 6 Artis Indonesia dengan Followers Instagram Terbanyak
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
Instagram is one of the social media that was founded by Burn Inc in 2010. Instagram allows its users to share our everyday photos and videos and can create videos, music, filters with user creativity. In Indonesia, the number of Instagram users is more than 300 million active users. make Instagram has many fans because of its features. There are many Instagram enthusiast platforms that make people develop creativity and popularity today, such as 6 Indonesian Artists with the most Instagram Followers, including: Gisella Anastasia, Laudya Cintya Bella, Syahrini, Prilly Latuconsina, Ayu Ting Ting, and Raffi Ahmad and Nagita Slavina . The purpose of this study is to calculate the performance of the Instagram account of 6 artists with the most followers in Indonesia. The method used in this study is quantitative exploratory, from the results of this study it can be shown that 6 Indonesian Artists with the most Followers with Video Comments to Followers Ratio Analysis prove the highest by Prilly Latuconsina with a value of 0.00002181.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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