Abstract
Cancer diseases are caused by combination of genetic, environmental, and lifestyle factors. Therefore, it is difficult for health organization to treat this disease. This study focuses on identifying the landscape of Cancer research by using bibliometric methods and social network analysis methods based on a number of research articles related to Cancer retrieved from PubMed. To deeply understand the landscape of research on this disease, we adopt productivity analysis which consists of author, university/institution, country and frequent MeSH terms analysis. We specifically perform the concept graph-based network analysis by applying four centrality measures and analyzing co-occurrence of MeSH terms. In the end, we propose a method to predict the Rising Star that may be the active researcher in the field of Cancer disease in the next few years. With this method, we can possibly find more academic cooperation via academic social networks. The encouraging results show that our work is highly feasible.
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