Prediction of Symptom-Disease Links in Online Health Forums

Social networks are structures that are used to model complex networks in different environments. The desire of reaching useful information by studying complex networks has made social network analysis an important research topic today. One of the most interesting subjects of social network analysis is link prediction. It estimates potential future connections by using the current state of the network. In this study, link prediction is made in bipartite graphs which is one of the social network structures. For this study, the network is first constructed with question and advise (generally disease) made on online health forum sites. Online health forum is a place where user can get his/her medical questions answered by real health professionals and other forum members. Then, symptoms of diseases are obtained by analyzing questions on online forum sites. Thus, a bipartite network consisting of questions and diseases corresponding to the obtained symptom data is constructed. In this network, link prediction has been made with internal links method. The results of the method have been compared with four of the other link prediction methods and it was found that this method has better performance than the other methods.

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