The goal of this research is to construct a semantic social web portal and to exploit the incentives of bridging Web 2.0 ↔ Web 3.0. The incentives will be justified when we can search information through this semantic social web portal compared with other systems that only provide simple tags (or keywords) search on Web 2.0 or ontology query on Web 3.0. Unless we can extend tags to have corresponding semantic context, the expressive power of tags is limited. In this study, we found that coherent taxonomies of blog articles can emerge from users tagging so relevant customized ontologies can be constructed.
3.1 Social Network Analysis
Social network analysis (SNA) is the quantity study of the relationships be-tween individuals or organization. By quantifying social network structures, we can determine where are the most important nodes in the network [24].
The implications of SNA usage are quite different when we apply SNA to different generation of Web.
• SNA for Web 1.0: The information on Web 1.0 is rather static so people only apply SNA on paper citation network or person relationship network to discover their stable relationships [18].
• SNA for Web 2.0: The nature of information flow on Web 2.0 is dynamic and user oriented. All of the tags, resources, and tagger’s profiles on Web 2.0 are dynamically created so the challenge to apply SNA for this platform is how can we timely extract the relationships between taggers with an-notated tags and their respective resources to enable effective information search [12].
• SNA for Web 3.0: We are aiming at bridging of Web 2.0 ↔ Web 3.0. The issues we consider including Web 2.0, Web 3.0, and SNA, are different from pure semantic social network approach shown in [19].
3.2 Blogs as Social Network
Applying SNA model to the blogsphere has revealed interesting findings about how individuals share information and interact socially online. Social relation-ships can be expressed online as different forms of blogs ties: blogroll links, citation links, and comment links [1]. We observed the WRETCH blog com-munities in terms of important SNA measures, such as indegree/outdegree, closeness/betweenness, and k-cores, to interpret their social implications. The basic idea is that blog article written by important blogger also becomes im-portant itself so we can reinforce the semantic search service capabilities for users to satisfy their interested from this perspective idea.
• Indegree and Outdegree: The higher indegree measure indicates the higher spread of blogger (or article) influence in the blogsphere. The indegree measures of the top 300 bloggers in the WRETCH BSP were shown as power law distribution. Contrarily, outdegree measure did not indicate any importance of a blogger in the community and its pattern did not appear as power law distribution either.
• Closeness and Betweenness: The higher closeness (or betweenness) of a blogger means it is in the social network center (or pivoting bridge) so the spread of influences of this blogger is significant in the community. We found that closeness (or betweenness) is similar to indegree but it incurs high computation overhead so we avoid computing this measure in our online information access.
• K-Cores: A k-core is a maximal subgroup in which each blogger (or ar-ticle) has at least degree k within the subgroup. Thus k-cores measure is effectively to demonstrate a particular subgroup cohesive relationship.
The common interests of a community derived from k-cores are important for topic-specific semantic social web query services to discover similar resources from this high cohesion level subgroup.
3.3 Semantic Social Web Query Services
We provide different level of semantic query services in our semantic social web portal: basic semantic query services, advanced semantic query services, and semantic social web query services:
• Basic semantic query services: The initial contribution of this article is to combine the tagging system’s folksonomy with ontology to achieve basic semantic query services. This service provides people or agents to effec-tively access clustering of blog information through tags and related tags.
• Advanced semantic query services via ontology+tags: In this service, user enables conceptual semantic query services with relevant tags. The con-ceptual semantics can be defined as a channel declared from ontology with relevant tags in the tags cloud. In other words, the search space for this
service is classified and focused so the search time is reduced and accuracy is also improved.
• Semantic social web query services via SNA+ontology+tags: In a blog ontology, we define properties to describe the relationships between blog-gers, tags, and articles. Additionally, the important SNA measurement attributes are also declared in a blog ontology. Therefore, we can leverage the power of SNA measures from dynamically generated relations through blogger’s daily activity events to enhance this service. We propose two possible scenarios for this service that could justify our hypothesis2:
1. Scenario One: I would like to search authors and their blog articles with “cuisine” tag paired with “restaurant” keyword in the associated title or content of the article collected from the entire blog community.
Furthermore, please present these authors’ names and their associated titles of article in a decreasing order of authors’ indegree measures:
prefix blog: <http://blog.nccucs.org/blog.owl#>
prefix rdf: <http://www.w3.org/19999/02/22-rdf-syntax-ns#>
SELECT DISTINCT ?Author ?Article WHERE
{?Article rdf:type blog:Article
?Article blog:has_articleTag blog:cuisine
?Article blog:has_author ?Person
?Person blog:person_ID ?Author
?Person blog:person_indegree ?Popularity FILTER {regex(?TitleOfArticle, "restaurant") ||
regex(?ContentOfArticle, "restaurant"))}
}
ORDER BY DESC (?Popularity)
2. Scenario Two: I would like to search blogger names and their articles from the cuisine channel for those of whom are known by authors pre-sented in scenario one. Furthermore, please present these blogger names and their associated titles of article in a decreasing order of authors’
indegree measures:
prefix blog: <http://blog.nccucs.org/blog.owl#>
prefix rdf: <http://www.w3.org/19999/02/22-rdf-syntax-ns#>
SELECT DISTINCT ?Author ?Friend ?TitleOfFriendArticle WHERE
{...
Codes Same As Scenario One ...
?Person blog:has_knows ?friend
?friend blog:person_ID ?Friend
2 The embedded codes are shown as SPARQL query language but users do not require to have knowledge of SPARQL syntax in order to execute semantic social web query services.
?FriendArticle blog:has_author ?friend
?FriendArticle blog:has_channel blog:CuisineChannel
?FriendArticle blog:article_title ?TitleOfFriendArticle
?FriendArticle blog:article_description ?ContentOfFriendArticle FILTER {regex(?TitleOfFriendArticle, "restaurant") ||
regex(?ContentOfFriendArticle, "restaurant"))}
}
ORDER BY DESC (?Popularity)
Compared with Technorati3, it only provides limited independent search services for user from his input blog posts, tags or directory where user can not have semantic (social web) query services for any possible relevant outputs using his previous search results. So user can not search the most influential blogger friend’s articles or he can not search high similarity articles from those bloggers with certain higher level of SNA indegree measures.