User Engagement Patterns in Viral Social Media Content: A Multinational Comparative Study Based on Interaction Ratios and Data Visualization - Robi Rojaya Simbolon; Sarah Fauziah Saefudin; Serani Arta Mauli Silalahi; Akhmad Bakhrun (SAINTIS Publishing, 2025)
This study explores user engagement patterns in viral social media content through a data visualization dashboard built with Power BI. The dataset comprises 5,000 viral posts across eight countries and four major platforms—Instagram, TikTok, X (Twitter), and YouTube—encompassing ten content hashtags. The analysis covers over 13 billion total views, with an average of 2.56 million views per post and an overall engagement rate of 22.27%. By visualizing metrics such as likes, comments, shares, and views, the dashboard enables multi-dimensional filtering and correlation analysis. The strongest finding is a perfect correlation (CC = 1.00) between views and all engagement types when filtered by content type, highlighting the pivotal role of format (e.g., YouTube Shorts, Photo posts) in driving interactions. High correlations were also found regionally, such as views and comments (CC = 0.92), and views and shares (CC = 0.91), suggesting significant influence of geographic and cultural factors.Further insights show that YouTube leads with 76.29% of total engagements in Brazil, while TikTok and Instagram dominate in the USA. Hashtags also contribute meaningfully, with view-comment correlation reaching 0.88. This dashboard proves valuable not only for tracking metrics but for generating actionable insights to inform content strategy, platform prioritization, and regional targeting. The findings affirm that virality is not incidental but influenced by measurable factors, making data-driven decisions essential for digital success.