Jennifer Golbeck, Matthew Rothstein. Linking Social Networks on the Web with FOAFhttp://www.foaf-project.org/: A Semantic Web Case Study. Proceedings of the Twenty-Third Conference on Artificial IntelligenceArtificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," (AAAI’08).
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ABSTRACT
One of the core goals of the Semantic Web is to store data in distributed locations, and use ontologies and reasoning to aggregate it. Social networking is a large movement on the web, and social networking data using the Friend of a Friendhttp://www.foaf-project.org/ (FOAF) vocabulary makes up a significant portion of all data on the Semantic Web. Many traditional webbased social networks share their members’ information in FOAF format. While this is by far the largest source of FOAF online, there is no information about whether the social network models from each network overlap to create a larger unified social network model, or whether they are simply isolated components. In this paper, we present a study of the intersection of FOAF data found in many online social networks. Using the semantics of the FOAF ontology, an ontology is a formal representation of knowledge as a set of concepts within a domain, and the relationships between those concepts. It is used to reason about the entities within that domain, and may be used to describe the domain. In theory, an ontology is a "formal, explicit ... and applying Semantic Web reasoning techniques, we show that a significant percentage of profiles can be merged from
multiple networks. We present results on how this affects network structure and what it says about relationships and individual behavior. Finally, we discuss the implications this has for using web-based social networking data to create intelligent user interfaces and social software.