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首页> 外文期刊>International Journal of Data Science and Analytics >ScholarRec: a scholars’ recommender system that combines scholastic influence and social collaborations in academic social networks
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ScholarRec: a scholars’ recommender system that combines scholastic influence and social collaborations in academic social networks

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Abstract Identifying and recommending influential scholars is one of the leading applications of scholarly data analytic. The existing methods to identify influential scholars focus on scholastic influence or social collaborations. In the former approach, scholar’s scientific productivity is anatomized, whereas in the latter one, scholar’s collaborations are analyzed. To accurately measure a comprehensive influence of a scholar, it is essential to combine scholastic influence and social collaborations. The purpose of this research is to develop a recommender system, ScholarRec, which combines scholastic influence and social collaborations; hence, accurately and comprehensively identifies influential scholars from Academic Social Networks (ASNs). To measure scholastic influence, apart from scientific productivity, ScholarRec incorporates scholar’s active engagement in information propagation and knowledge dissemination. To measure the degree of social collaborations, ScholarRec explores follower and following connections among scholars instead of traditional co-author and co-citation relations. The performance of ScholarRec is evaluated on two well-known ASNs, ResearchGate (RG) and Academia. User demographic features demonstrating scholar’s scholastic and social contributions are collected for a set of scholars. To identify the significance of each feature included in ScholarRec, a weighting scheme is developed. It assigns an appropriate weight to each feature based on its significance in influence calculation. The weighted features help in generating unique ranks to influential scholars. The developed weight assignment technique also makes ScholarRec applicable to different ASNs with diverse features. The results reveal that ScholarRec accurately identifies and uniquely recommends influential scholars for RG and Academia.

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