Efficient assembly of social semantic networks

Abstract

Social bookmarks allow Web users to actively annotate individual Web resources. Researchers are exploring the use of these annotations to create implicit links between online resources. We define an implicit link as a relationship between two online resources established by the Web community. An individual may create or reinforce a relationship between two resources by applying a common tag or organizing them in a common folder. This has led to the exploration of techniques for building networks of resources, categories, and people using the social annotations. In order for these techniques to move from the lab to the real world, efficient building and maintenance of these potentially large networks remains a major obstacle. Methods for assembling and indexing these large networks will allow researchers to run more rigorous assessments of their proposed techniques. Toward this goal we explore an approach from the sparse matrix literature and apply it to our system, GiveALink.org. We also investigate distributing the assembly, allowing us to grow the network with the body of resources, annotations, and users. Dividing the network is effective for assembling a global network where the implicit links are dependent on global properties. Additionally, we explore alternative implicit link measures that remove global dependencies and thus allow for the global network to be assembled incrementally, as each participant makes independent contributions. Finally we evaluate three scalable similarity measures, two of which require a revision of the data model underlying our social annotations.

A Mapping Study to Investigate Spam Detection on Social Networks

“…Flagging users as spammers is the approach taken by some social networks regarding spam detection, such as BibSonomy. This approach is intuitive and easy from an administrator's point of view [33].…”

“…• Limitation that restrict the practical use of performance measurement on spam detection [33] RQ 3. Are the limitations of the current research?…”

“…The main aim of this review is to understand, classify and analyze the existing spam detection on social networks for measuring the quality of spam detection on social networks and its architectural framework, to direct and support future research, while other reviews [9] [2] [7], [74] and [33] aim mainly at provide an overview of quality measure and evaluations. Certainly a difference in goals leads to a different focus.…”

“…Spam detection concept and framework from the perspective of defining Spam detection on social networks Several definition of spam detection are given [9], [33], [7], [74]; each of definitions states different characteristics for the framework of spam detection on spam detection.…”

User-induced links in collaborative tagging systems

“…Firstly, given the large number of tags that have been assigned to the documents, implicit links can be found by calculating the similarity between the sets of tags assigned to the documents. For example, [11] describe a system called GiveALink, which involves a global semantic similarity network to capture relationships among resources, and suggest that semantic similarity can be treated as an alternative way of navigating the Web by suggesting users to visit a page similar to the one being visited.…”