Youtube_​Trending_​Analysis

<p><strong><em>K-Means </em></strong><em>clustering of 16,200 YouTube trending videos (Brazil, Feb 2026) to group them into four engagement tiers.</em></p><p><strong><em>What it does:</em></strong><em> filters the data down to views, likes, dislikes and comments, scales them to a 0–1 range, clusters them with k-Means (k = 4), plots the clusters, and exports a summary table with the average engagement and size of each group.</em></p><p><strong><em>Finding: </em></strong><em>engagement is very uneven. 14,401 videos fall in the minimal tier, while only 35 reach the high-engagement tier.</em></p><p><strong><em>Note: </em></strong><em>dislikes are all zero in this dataset, so the clusters are really driven by views, likes and comments. Data: YouTube Trending Video Dataset on Kaggle. Built in KNIME Analytics Platform.</em></p>