Capretz, “Integrating Recommender Information in Social Ecosystems Decisions

The exploration of online social networks whose members share mutual recommendations and interactions is a time-dependent and contextual-based process which aims to predict the social status among members, ultimately improving the network's discoverability to achieve societal gain. To address the difficulties associated with the process, this article presents an integrated recommender model whose statements are time-dependent, interaction-aware, and social context-sensitive. The originality of the proposed model stems from the integration of the predictive recommender, social networks, and interaction components. Each model is developed based on: (1) a time history and decay algorithm to consider the decreasing intensity of recommendations among members over time; (2) a predictive aggregating function for improved assessment o