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This project aims at developing an RDF graph building service for Cyber Infrastructure for Network Science (CINET). The purpose of this service is to do web crawling and find digital contents related to user requests. More specifically, the type of contents to be collected should be related to epidemiology. Eventually the service should deliver an RDF network of digital contents that can be stored on CINET for analysis. Simply using a search engine such as Google, or a web crawler in an undirected way, won't be able to satisfy the requirements of this problem, due to the lack of organization of the results and the ambiguity of the information. Our service should present to users networks of interconnected digital objects, which are organized based on their topics. In the results, all digital objects are connected as a network of related contents based on a user's request. In addition to that, those who are closer to a topic will be more strongly connected in a sub-network. The developed topic modeling approach emulates human behavior when searching relevant research papers. It automatically crawls the DBLP bibliography website and constructs a network of papers based on a user query.