ANALYZING SOCIAL NETWORKS: IDENTIFYING TRENDS AND USER CLUSTERS

Authors

  • Aizhan Adilkhan Master's Degree in Technology Management, University of California Santa Barbara, USA Author

Keywords:

Social network analysis; online community; clustering method; data clustering; graph model; online communities; features of cluster analysis.

Abstract

Social media has undoubtedly become one of the major sources of information and information interaction in the modern world. As billions of users communicate daily on platforms such as TikTok, Facebook, Instagram, Twitter, etc., the problems of detecting trends and hidden structure of these networks have both scientific and practical significance. This paper discusses the critical aspects of community detection, methodologies, algorithms and tools used today, as well as the real-world impact and future prospects of this interesting research area.

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Published

2025-06-04

Issue

Section

Articles

How to Cite

ANALYZING SOCIAL NETWORKS: IDENTIFYING TRENDS AND USER CLUSTERS. (2025). Modern American Journal of Engineering, Technology, and Innovation, 1(2), 236-245. https://usajournals.org/index.php/2/article/view/255