A Treatise to Metrics and Frameworks for Semantic Social Networks: A Systematic Literature Review

In the semantic web, each piece of data, referred to as metadata, is accompanied by meaningful data. This information is then used by machines to make calculations-based decisions. This implementation of semantic web methods in social networks shapes the premise of Semantic Social Network (SSN). SSN creates a virtual group of friends and family where people can share resources, thoughts, by staying associated with their loved ones. This semantic social data can be used to gauge different conduct ascribes of SSN individuals utilizing measurements. The extricated results from these measurements can help experts of SSN to settle on better choices in giving offers, rewards, badges to individuals. There are frameworks available for semantic social network analysis as well. A systematic literature review (SLR) is presented in this paper by leading an overview of available metrics to calculate semantic social network member traits and frameworks used for social network analysis. The basic SLR has been aggregated by looking into research articles distributed in all around presumed scenes somewhere in the range of 2000 and 2020. A sum of 22 papers was painstakingly filtered through an orderly interaction and grouped appropriately. The essential target of this precise investigation is the assortment of all-important examinations on currently available metrics to calculate members ascribes of the semantic social network and the frameworks used for semantic network analysis. As a result, six metrics and nine frameworks are extracted and presented. Moreover, this paper also discusses possible ways to improve metrics for a better semantic social network (SSN) analysis. In recent years, countless efforts have been made in the Semantic Social Network Analysis area to measure ascribes and define frameworks. Consequently, it is imperative, to sum up, gather, break down, and group the research about this area. The reason for this research is to introduce an extensive deliberate literature review for the aggregation of metrics and frameworks used in semantic social network analysis SSNA