SM-ILE: a framework for intrusion detection in an informal social environment based on users' traces

Social media is a novel technology, which uses internet and Web 2.0. It allows users to create and participate to several communities through different functionalities such as communication, collaboration, sharing, updating and interaction. The use of social media in learning field has been increased. Therefore, most educational institutions nowadays are using these technologies to enhance users' engagement. We propose in this paper an informal learning environment called SM-ILE (a trace-based framework for social media as an informal learning environment). This model aims at detecting intrusion learners to improve their learning by recommending to them good collaborators and relevant resources. Moreover, we analyse and qualitatively compare social media and informal learning related works. The proposed algorithm was applied to an informal social environment (http://sncl.ga). An experiment was conducted in a group of students in an Algerian university. The obtained results from this experiment were good and very efficient.