Mapping the Intellectual Structure of Epidemiology with Use of Co-word Analysis

• Published in: Journal of biostatistics and epidemiology Vol. 5; no. 3
• Main Authors: Baziyad, Hamed, Shirazi, Saeed, Hosseini, Seyedmohammadreza, Norouzi, Rasoul
• Format: Journal Article
• Language: English
• Published: Tehran University of Medical Sciences 07.07.2020
• Subjects: Co-word analysis; Graph mining; Intellectual structure of epidemiology; Social network analysis; Text mining
• ISSN: 2383-4196; 2383-420X; 2383-420X
• DOI: 10.18502/jbe.v5i3.3618

Background and Aim: The existence of an intellectual structure for every field is essential for managers and scholars. Intellectual structures provide a comprehensive map of knowledge that can guide researchers and managers to have a better view of their fields. Besides, with high-speed and massive amounts of data and information generation, reading and surveying of all resources are severely tricky. Intellectual maps solve this problem and make a situation for control and monitoring this voluminous and high-speed generated data. Epidemiology is regarded as one of the exciting fields which many researchers focused on it. A study of the structure and criteria of different epidemiological fields has not been done yet. Indeed, there is no serious effort for knowledge discovery of hidden information on epidemiological texts. Methods: In this paper, in order to survey this field, an intellectual structure is provided using co-word analysis. Utilizing co-word analysis discloses relationships and structure among research subjects and topics in a field. Results: Finally, four main clusters were determined, namely: genetic (with 30.53% of surveyed papers), illness (29.47%), modeling (23.16%), and prevention (16.84%). Conclusion: According to epidemiology co-word network, epidemiology area has not been studied from enough different areas, especially from novel technologies.