计算机科学
社交网络(社会语言学)
互联网
数据科学
质量(理念)
群落结构
复杂网络
数据挖掘
万维网
社会化媒体
数学
哲学
认识论
组合数学
作者
Kulkarni Varsha,Kiran Kumari Patil
标识
DOI:10.1109/icict48043.2020.9112563
摘要
The technology is making its road of development continuously and all the users are enjoying the benefits from it and leading an easy life. With the rise in usage of internet, many people join online social networks to connect with the world, share their views, and interact with others. Thus, the increasing sizes of social networks are becoming complex and are involving a huge amount of data. Mining these data has become one of the domains in information technology. The fundamental application and/or also active research from this data is discovering meaningful communities from interaction among different people of a huge network. The algorithms on community detection are very useful & necessary to find the pattern or structure of the social network, analyze the social network, find out the relationship between two people and also control the sentiments of the people. The quality of detected communities is also measured by using different parameters. This work starts with an explanation on the concepts of online social networks, communities and community detections then survey on the different community detection algorithms have been done based on the different categories.
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