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Detection and recommendation of experts/authorities of Mendeley and Twitter topics for learning stimulation

Abstract:

Nowadays, life unfolds in a digitised world, in which, each person can have access to a huge amount of information through the use of Internet. In this situation, most of daily activities are being influenced by a new kind of society that allows ubiquitous and instantaneous interaction among its members. The creation of social platforms (SPs) has strengthened human relationships at such point that any person can globalise their knowledge, experience, and opinion about a specific topic. According to the society, this can be seen as an interpersonal relationships evolution; however, this sets up an over-information problem. Looking at the educational field, such problem is a sensitive subject due to students need only experts/authorities knowledge. In order to provide a solution to this situation, in this paper, we propose the development of an experts/authorities recommender system, based on Mendeley and Twitter, to improve educational processes.