With the emergence of Internet technology, users have started exploring, connecting and socializing themselves on the social media anywhere and anytime. Social networks have reformed the means we communicate. Online social networks are gaining importance due to the generation of large metadata that was never possible before. With this metadata from social networks, recommender systems gain benefit to determine rating preferences of users. Nowadays, social networks are also becoming useful in academics. They promote collaborative learning between students. This paper inspects the role of social networks in recommending projects to students. We propose a system that uses social network information of students to generate recommendations. We use several factors which play essential role in project recommendations. The contextual information from user profiles and the tags that are used by projects for reviewing, rating, tagging or contributing are employed. These tags are then used to extract the most relevant tags on the basis of the factors considered.

Recommender system, Social networks, Collaborative learning

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