Optimizing Graph Theory Algorithms for Social Network Analysis

Q4 Mathematics
S. Sahoo, Sasmita Mishra
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引用次数: 0

Abstract

Social network analysis (SNA) leverages graph theory to understand and visualize the complex relationships and structures within social networks. This research paper explores the optimization of graph theory algorithms tailored for SNA, focusing on efficiency improvements in handling large-scale networks. The study reviews key graph theory concepts, identifies common challenges in SNA, and evaluates various optimization techniques. Practical applications and case studies are presented to demonstrate the impact of these optimizations in real-world scenarios.
为社交网络分析优化图论算法
社会网络分析(SNA)利用图论来理解和可视化社会网络中的复杂关系和结构。本研究论文探讨了为 SNA 量身定制的图论算法的优化问题,重点是提高处理大规模网络的效率。研究回顾了关键图论概念,确定了 SNA 中的常见挑战,并评估了各种优化技术。论文还介绍了实际应用和案例研究,以展示这些优化技术在现实世界中的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
0.30
自引率
0.00%
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0
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