Extracted Social Network Mining
This work addresses the extraction of social networks from web data, but it appears incremental as it applies existing set theory methods to a new context without clear benchmarks or broad impact.
The authors tackled the problem of mining social networks from web data by using a search engine to define social actors and relationships through set theory, resulting in a representation of social behaviors and connections based on web occurrences.
In this paper we study the relationship between the resources of social networks by exploring the Web as big data based on a simple search engine. We have used set theory by utilizing the occurrence and co-occurrence for defining the singleton or doubleton spaces of event in a search engine model, and then provided them as representation of social actors and their relationship in clusters. Thus, there are behaviors of social actors and their relation based on Web.