Evaluating reliability of question-disease relations in online health forms: A link prediction approach - Kaya, Buket; Gundogan, Esra (Elsevier, 2018)
The Internet has become an indispensable part of human life in today. People can now easily find answers to questions they are curious about via the internet. The short, effortless and free way that the Internet provides is extremely attractive for people to have an idea in subjects they wonder related to their health. There are many online health forums where people can ask questions answered by health professionals. Every day, people ask thousands of questions on these sites and get answers about which diseases their complaints may be related to. The frequent use of online forum sites by people has led to the selection of these forums as data source for this study, and analysis of reliability. Firstly, in this study, link prediction in bipartite social networks, where intensive works have been done and it is applied on many areas nowadays, is tried to be carried out on question-disease bipartite network constructed with data obtained from analysis of online health forums whose use rate increase substantially. For this purpose, a novel link prediction method called as intensive link prediction is proposed, and prediction success of this method is compared with five of similarity-based link prediction methods. Better results have been obtained with the proposed method than the other methods. Then, the accuracy of the answers given to the users on online health forums which received intense interest are tested. The reliability of online health forums is measured by the accuracy analysis performed.
Keywords: Online health forums; Question-disease relations; Link prediction; Social network analysis