Community Detection Methods and Tools for Various Complex Network

Abstract

The analysis of complex networks like social, biological network is a new era of research in information mining. The analysis of social networks has gained considerable attention in the current era, mainly due to the high growth of social networks and content exchange sites. A social network can be seen as a complex interconnection of social entities in terms of vertex and nodes. The detection of the community is the task of grouping social entities based on the linking of nodes and relationships. Most of the research has been done on the basis of grouping algorithms and extraction techniques. There are many problems associated with the task of researching social group and network analysis, such as the grouping of nodes, community mining, the generation of graphics, the prediction of links. The detection of the community in the mining of social networks is different from the traditional grouping methods. Community detection is a way to recognize the network nodes in a group or community within which the property of identified vertices is maximized in terms of similarity. Communities can have concrete applications.

Local Community Detection: A Survey

“…As can be inferred, these tools are not specifically designed for detecting local communities, but for detecting communities in general. Of course, researchers can use such tools for LCD, and here we present several that are either packages based on graphical user interfaces (GUIs) or libraries in scripting/programming languages [23], [149]. In Table 13 we present in alphabetical order the most popular tools used in network community detection, along with their type (GUI or library), the platform requirements to be installed and their licenses.…”