An implementation in the health sector with social network analysis

Social network analysis is a type of analysis that examines social relationships. Due to increasingly complex structure of relations in recent years, it is extremely essential to make inferences by applying the analysis. This type of analysis, as in other fields, appears in the health sector with various methods and the interest in this field is gradually increasing. In terms of health, heart and heart diseases have an important place in these fields. Millions of people dealing with heart disease due to several factors lives in the world and especially many people lose their lives due to heart attack in Turkey. For this reason, the focus of the thesis work is on the causes of the heart attack and the analysis of their networks. Therefore, the network status of the causes of the heart attack on Twitter has been investigated. Required data was collected from Twitter using NodeXL Pro program and analyses were compared. The network with the most Twitter users and connections is relative disease story network. While the most central networks are the high cholesterol and stress networks, the average clustering coefficients are quite low for all networks. The networks with the shortest geodesic distance are high cholesterol, smoking, inactivity and stress networks and Twitter users on these networks are in easier communication while sharing information.