社会网络分析方法与算法综述

Ranjana Sikarwar, H. K. Shakya, S. Singh
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引用次数: 2

摘要

在过去的几年里,Facebook、Twitter和Instagram等基于社交网络的应用程序被所有年龄段和背景的人使用。它是一个丰富的在线用户共享知识的平台。这些信息以感觉、观点、兴趣、事件或评论的形式以大量和各种形式的数据共享。许多多学科研究人员进行了研究,以找出社交媒体数据的商业价值。这种对研究的兴趣背后的原因是从网络访问数据,处理数据,并从网络中提取有用信息的影响。研究人员对信息传播、群体关系分析等主题进行了研究和探索,以满足不同的应用需求。本文对社交网络中的社区检测问题进行了调查和分析,并对相关领域的研究进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review on Social Network Analysis Methods and Algorithms
Social network-based applications like Facebook, Twitter, and Instagram have been used by people of all age groups and backgrounds for the last few years. It is a rich platform for sharing knowledge amongst users online. This information is shared as feelings, opinions, interests, events, or comments in large volumes and varied forms of data. Many multidisciplinary researchers have conducted studies to find out the commercial values of social media data. The reason behind this interest in research is an affluence to access data from the web, process it, and pull-out useful information from the web. Researchers have worked upon and explored the topics like information spreading, relationship analysis in groups for some or other applications. This review paper conducts a survey on community detection problem in social networks, its analysis, and a study of research done on related areas.
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