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...

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Bibliographic Details
Published in:2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) pp. 876 - 880
Main Authors: Gündoğan, Esra, Kaya, Buket, Kaya, Mehmet
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 31.07.2017
Series:ACM Conferences
Subjects:
Applied computing
Applied computing > Life and medical sciences
Applied computing > Life and medical sciences > Consumer health
Applied computing > Life and medical sciences > Health care information systems
Applied computing > Life and medical sciences > Health informatics
Bipartite graph
Bipartite graphs
Complex networks
Diseases
Information systems
Information systems > Information systems applications
Information systems > Information systems applications > Data mining
Link prediction
Mathematical model
Mathematics of computing
Mathematics of computing > Discrete mathematics
Mathematics of computing > Discrete mathematics > Graph theory
Online health forums
Prediction methods
Probability
Social network analysis
Social networking (online)
Link prediction
Social network analysis
Bipartite graphs
Online health forums
ISBN:1450349935, 9781450349932
ISSN:2473-991X
Online Access:Get full text
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Summary: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.
ISBN:1450349935
9781450349932
ISSN:2473-991X
DOI:10.1145/3110025.3119399