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The increased usage of information technologies in educational tasks resulted in high volume of data, exploited to build analytical systems that can provide practical insight in the learning process. In this paper, we propose a method of running social network analysis on multiple data sources (academic years, communication tools). To achieve this, the collected data that describe social interactions were converted into a common format by employing a prior developed semantic web educationaldoi:10.2498/cit.1002645 fatcat:gmumjqkynvglla7ia2snbyfmu4