Most people are more or less related to the web by participating in a kind of social networking site. Semantic Web technology plays a crucial role in these sites as they contain an enormous amount of data about persons, pages, events, places, corporations, etc. This research is a Semantic Web application designed to create a new semantic social community called Socialpedia. It links the already existing social public information to the newly public ones. This information is linked with different information on the web to construct a new immense data container. The resulting data container can be processed using a variety of Semantic Web techniques to produce machine-understandable content. This content shows the promise of using integrated data to improve Web search and Web-scale data analysis, unlike conventional search engines or social ones. This community involves obtaining data from traditional users known as contributors or participants, linking data from existing social networks, extracting structured data in triples using predefined ontologies, and finally querying and inferring such data to obtain meaningful pieces of information. Socailpedia supports all popular functionalities of social networking websites besides the enhanced features of the Semantic Web, providing advanced semantic search that acts as a semantic search engine.
