Social Network Analysis - A Survey

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkSocial Network Analysis is attracting growing attention as social networking sites and their enabled applications transform and impact society. This paper aims to provide a comprehensive review of social network analysis state of the art research and practice. In the paper the authors’ first examine social networking and the core concepts and ingredients of social network analysis. Secondly, they review the trend of social networking and related research. The authors’ then consider modelling motivations, discussing models in line with tie formation approaches, where connections between nodes are taken into account. The authors’ outline data collection approaches along with the common structural properties observed in related literature. They then discuss future directions and the emerging approaches in social network analysis research, notably semantic social networks and social interaction analysis

Towards disambiguating social tagging systems

Social tagging to annotate resources represents one of the innovative aspects introduced with Web 2.0 and the new challenges of the (semantic) Web 3.0. Social tagging, also known as user-generated keywords or folksonomies, implies that keywords, from an arbitrarily large and uncontrolled vocabulary, are used by a large community of readers to describe resources. Despite undeniable success and usefulness of social tagging systems, they also suffer from some drawbacks: the proliferation of social tags, coming as they are from an unrestricted vocabulary leads to ambiguity when determining their intended meaning; the lack of predefined schemas or structures for inserting metadata leads to confusions as to their roles and justification; and the flatness of the structure of the keywords and lack of relationships among them imply difficulties in relating different keywords when they describe the same or similar concepts. So in order to increase precision, in the searches and classifications made possible by folksonomies, some experiences and results from formal classification and subjecting systems are considered, in order to help solve, if not to prevent altogether, the ambiguities that are intrinsic in such systems. Some successful and not so successful approaches as proposed in the scientific literature are discussed, and a few more are introduced here to further help dealing with special cases. In particular, we believe that adding depth and structure to the terms used in folksonomies could help in word sense disambiguation, as well as correctly identifying and classifying proper names, metaphors, and slang words when used as social tags