Online Socialnetwork Internetworking Analysis

Online social networks (OSNs) contain data about users, their relations, interests and daily activities and the great value of this data results in ever growing popularity of OSNs. There are two types of OSNs data, semantic and topological. Both can be used to support decision making processes in many applications such as in information diffusion, viral marketing and epidemiology. Online Social network analysis (OSNA) research is used to maximize the benefits gained from OSNs’ data. This paper provides a comprehensive study of OSNs and OSNA to provide analysts with the knowledge needed to analyse OSNs. OSNs’ internetworking was found to increase the wealth of the analysed data by depending on more than one OSN as the source of the analysed data. Paper proposes a generic model of OSNs’ internetworking system that an analyst can rely on. Two different data sources in OSNs were identified in our efforts to provide a thorough study of OSNs, which are the OSN User data and the OSN platform data. Additionally, we propose a classification of the OSN User data according to its analysis models for different data types to shed some light into the current used OSNA methodologies. We also highlight the different metrics and parameters that analysts can use to evaluate semantic or topologic OSN user data. Further, we present a classification of the other data types and OSN platform data that can be used to compare the capabilities of different OSNs whether separate or in a OSNs’ internetworking system. To increase analysts’ awareness about the available tools they can use, we overview some of the currently publically available OSNs’ datasets and simulation tools and identify whether they are capable of being used in semantic, topological OSNA, or both. The overview identifies that only few datasets includes both data types (semantic and topological) and there are few analysis tools that can perform analysis on both data types. Finally paper present a scenario that shows that an integration of semantic and topologic data (hybrid data) in the OSNA is beneficial.