Tag Ranking Multi-agent Semantic Social Networks

Abstract

Social Media has become one of the most popular platforms to allow users to communicate, and share their interests without being at the same geographical location. With the rapid growth of Social Media sites such as Facebook, LinkedIn, and Twitter, etc. There is vast amount of user- generated content. Thus, the improvement in the information quality has become a great Challenge to all social media sites, which allows users to get the desired Content or be linked to the best link relation using improved search / link technique. So introducing semantics to media networks will widen up the representation of the social media networks. Semantic Social Networks representation of social links will be extended by the semantic relationships found in the vocabularies which are known as (tags) in most of social media networks. This paper proposes a new model of semantic social media networks from the perspective of multi-agent systems. The multi-agent system is composed of two main functionalities: semantic indexing and tag ranking.