Open AccessApplication of Clustering to Analyze Academic Social Networks
Author(s) -
Sobha Rani K,
Raju Kvsvn,
V. Valli Kumari
Publication year - 2013
Publication title -
international journal of web and semantic technology
Language(s) - English
Resource type - Journals
eISSN - 0976-2280
pISSN - 0975-9026
DOI - 10.5121/ijwest.2013.4202
Subject(s) - cluster analysis , computer science , social network analysis , artificial intelligence , world wide web , social media
Social network is a group of individuals with diverse social interactions amongst them. The network is oflarge scale and distributed due to involvement of more people from different parts of the globe.Quantitative analysis of networks is need of the hour due to its’ rippling influence on the network dynamicsand in turn the society. Clustering helps us to group people with similar characteristics to analyze thedense social networks. We have considered similarity measures for statistical analysis of social network.When a social network is represented as a graph with members as nodes and their relation as edges, graphmining would be suitable for statistical analysis. We have chosen academic social networks and clusterednodes to simplify network analysis. The ontology of research interests is considered to measure similaritybetween unstructured data elements extracted from profile pages of members of an academic socialnetwork