Web Mining and Social Networking: Techniques and ... - tud.ttu.ee

26 2 Theoretical BackgroundsBetweenness and ClosenessBetweenness and Closeness are both the magnitude measures that reflect the relationshipsof one vertex to the others in the network.CliqueClique represents, in the context of social network, a sub-set of a network in whichvertexes are more closely connected to one another than to other members of thenetwork. In some extents, clique is a similar concept to community, which meansthe members within the same group have a high similarity in some aspects, such ascultural or religious belief, interests or preferences and so on. The clique membershipgives us a measure of how likely one vertex in the network belongs to a specific cliqueor community.2.8.2 Social Network over the WebInteractions and relationships between entities can be represented with an interconnectednetwork or graph, where each node represents an entity and each link representsan interaction or a relationship between a pair of entities. Social networkanalysis is interested in studying social entities (such as people in an organization,called actors) and their interactions and relationships by using their network or graphrepresentations.The World Wide Web can be thought of as a virtual society or a virtual socialnetwork, where each page can be regarded as a social actor and each hyperlink asa relationship. Therefore, results from social network analysis can be adapted andextended for use in the Web context. In fact, the two most influential link analysismethods, PageRank and HITS, are based on the ideas borrowed from social networkanalysis.Below, two types of social network analysis, i.e. centrality and prestige, whichare closely related to hyperlink analysis and Web search, are introduced. Both ofthem are measures of degree of prominence of an actor in a social network.CentralityIntuitively, important or prominent actors are those that are linked or involved withother actors extensively. Several types of centrality are defined on undirected anddirected graphs. The three popular types include degree centrality, closeness centrality,and betweenness centrality. For example, using a closeness centrality, the centerof the network is defined based on the distance: an actor i is central if it can easilyinteract with all other actors. That is, its distance to all other actors is short. Let theshortest distance from actor i to actor j be d(i, j), measured as the number of linksin a shortest path. The closeness centrality C c (i) of an actor i is defined asC c (i)=(n − 1)/∑ j=1,...,nd (i, j) (2.15)