Discovering Joint Research Topics Based on Social Networks Using A Traversing Algorithm

Researchers need to examine trends and novel technologies of their own research areas. With the rapid growth of the Web, however, large amounts of information are generated daily. Therefore, it is generally difficult for researchers to obtain information related to their own areas and novel technologies from huge data residing in the Web. Furthermore, they often try to apply the technologies of their own fields to other different areas to solve existing difficult problems or improve the performance of existing systems. Hence, it is important to discover joint research topics in which technologies of particular research areas are applied to other different areas in order to recognize and follow various current trends. In this paper, we propose a novel method to discover joint research topics using a traversing algorithm based on social networks representing the relations among the authors of papers, and describe some experimental results to show the effectiveness of the proposed method.