Much interest is currently focused on social network services such as Facebook and Twitter. Social media and social network change the method of human communication and will eventually change business methods as well. Research on social network has been used in various fields including management and applied science. However, studies on the semantic association in the network are rare. Semantic associations between entities are necessary for future business and social studies.
In this research, the ontology-based social network analysis is performed. A new method to compute the strength of association among entities is proposed. Using the proposed method, a new social network is extracted.
To evaluate the proposed method, experiments are performed. A group of university students are selected, and their social connections with other students are evaluated. The human responses are compared to the results of the extracted social network. The proposed method can be used to extract a social network from associations among entities in an ontology-based knowledge base.
[1]
Peter Mika.
Social Networks and the Semantic Web (Semantic Web and Beyond)
,
2007
.
[2]
Huilin Wang,et al.
Discovering Associations among Semantic Links
,
2009,
2009 International Conference on Web Information Systems and Mining.
[3]
Wolfgang Nejdl,et al.
Semantically Rich Recommendations in Social Networks for Sharing and Exchanging Semantic Context
,
2005
.
[4]
J. A. Barnes.
Class and Committees in a Norwegian Island Parish
,
1954
.
[5]
Steven B. Andrews,et al.
Structural Holes: The Social Structure of Competition
,
1995,
The SAGE Encyclopedia of Research Design.