Volume 18 , Issue 2 , PP: 35-42, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Haitham S. Hasan 1 *
A considerable number of individuals concentrate their engagement on social media sites, notably Instagram, YouTube, and Facebook, where they may adeptly exploit their popularity. A considerable volume of research studies has been conducted across diverse social networks to examine user profiles and their relationship with popularity. The primary emphasis of research concerning social media has centered on theme analysis, encompassing domains such as health, creativity, and awareness. This study utilizes K-means clustering to classify social media articles and determine the characteristics that contribute to their popularity. Gathered data from publications by international influencers during an eight-month duration. Producing roughly 161 posts daily and around 1092 posts monthly seeks to improve metrics including views, likes, and dislikes on social media. This strategy is designed to facilitate the growth of the platform's popularity, thereby maximizing visibility and outreach. The analysis focused on three factors: virility, appeal, and publicity rates. Classified the posts into five fundamental groups: casual, quality, number, support, and leader. The study yielded important findings on optimal publication timing, ideal video length, follower metrics, biography and caption lengths, and hashtag utilization. Researchers found some interesting things that will help people who use social media and brand owners make better marketing plans.
Data Science Techniques , Data Pattern Identification , K-mean cluster , Statistics , Machine Learning
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