Social Network Extraction: Superficial Method and Information Retrieval
This addresses the challenge of analyzing social networks for government issues, but appears incremental as it compares existing approaches without clear new breakthroughs.
The paper tackles the problem of extracting social networks from unstructured web documents by proposing an Information Retrieval-driven method to handle feature heterogeneity, comparing approaches for extracting social relations including strength relations and those based on online academic databases.
Social network has become one of the themes of government issues, mainly dealing with the chaos. The use of web is steadily gaining ground in these issues. However, most of the web documents are unstructured and lack of semantic. In this paper we proposed an Information Retrieval driven method for dealing with heterogeneity of features in the web. The proposed solution is to compare some approaches have shown the capacity to extract social relation: strength relations and relations based on online academic database.